# Altimate AI

> Altimate builds agentic tooling for data engineering: Altimate Code (an open-source agentic harness), Power User for dbt (VS Code extension), and an enterprise platform for Snowflake and Databricks cost optimization, lineage, and governance.

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## Overview

- [Altimate.ai | Best AI Data Engineering Agent](https://altimate.ai/index.md): AI data engineering agent you can trust in production: bring context, governance, and execution together; build and manage data workflows safely. Free to start.

## Products

- [Altimate Code | Better than Claude Code for Data Engineering](https://altimate.ai/products/altimate-code.md): Use Altimate Code for better results than Claude Code and Cursor on data engineering. Build and manage SQL, dbt, lineage, and warehouse workflows, open source.
- [Altimate Lite for Snowflake | Native App Cost Optimization](https://altimate.ai/products/altimate-lite.md): Altimate Lite is a Snowflake Native App that auto-tunes your warehouses as workloads change and breaks down your AI costs by model, user, and service.
- [dbt Power User: Free VS Code Extension for dbt](https://altimate.ai/products/dbt-power-user.md): dbt Power User is a free, open source VS Code extension for dbt Core, Cloud and Fusion. Column lineage, autocomplete, AI docs and query preview. 1M+ installs.

## Platform

- [Agentic Data Engineering Platform](https://altimate.ai/platform.md): Build with trusted data agents on an agentic data engineering platform with context, governance, and execution infrastructure for reliable data workflows.

## Use Cases

- [Use Cases](https://altimate.ai/use-cases.md): Six use cases, one platform. Build pipelines, migrate workloads, ship data apps, manage infrastructure, optimize costs, and enforce governance.
- [Databricks Cost Optimization & Pricing Model](https://altimate.ai/use-cases/altimate-for-databricks.md): Cut Databricks costs 20–35% by right-sizing job clusters, SQL warehouses, and all-purpose compute automatically. No serverless migration required.
- [Snowflake Cost Management and Query Optimization](https://altimate.ai/use-cases/altimate-for-snowflake.md): Optimize Snowflake costs and queries with AI-powered tools for adaptive compute, warehouse efficiency, and smarter data workloads while maintaining performance.
- [Analytics Engineering](https://altimate.ai/use-cases/analytics-engineering.md): The dbt development app for analytics engineers. Generate dbt models, write docs, create tests, and enforce best practices from your IDE. 1M+ installs.
- [Workload Migration](https://altimate.ai/use-cases/workload-migration.md): Migrate workloads 10 to 15 times faster with zero business logic lost. The Data Pipelines Migration app handles SQL transpilation, rebuilds, and validation.

## Benchmarks

- [Altimate Code Benchmarks: ADE-Bench and DAB Bench Results](https://altimate.ai/benchmarks.md): altimate-code scores 78.0% on ADE-Bench and 71.7% Pass@1 on DAB Bench, published across Snowflake, DuckDB, PostgreSQL, MongoDB, and SQLite.
- [ADE-Bench Results](https://altimate.ai/benchmarks/ade-bench.md): ADE-Bench: altimate-code hits 74.4% on Snowflake with Sonnet 4.6 and 78.0% on DuckDB with DeepSeek V4 Pro, ahead of Cortex Code CLI, dbt Labs, and Claude Code.
- [DAB Benchmark (DataAgentBench) Results](https://altimate.ai/benchmarks/dab-bench.md): DataAgentBench (DAB) benchmark results. Altimate Code scores 71.7% Pass@1 across PostgreSQL, MongoDB, SQLite and DuckDB.

## Comparisons

- [Altimate AI Comparisons](https://altimate.ai/comparisons.md): Side-by-side Altimate AI comparisons against Snowflake Cortex Code, dbt Wizard, Claude Code, Keebo, Revefi and more. Capability tables and ADE-Bench scores.
- [Altimate AI vs Capital One Slingshot](https://altimate.ai/comparisons/altimate-vs-capital-one-slingshot.md): Altimate AI vs Capital One Slingshot: autonomous savings vs manual approval, optimization below the warehouse, and an open self-serve AI-agent platform.
- [Altimate AI vs Claude Code](https://altimate.ai/comparisons/altimate-vs-claude-code.md): Altimate AI vs Claude Code. A strong general coding agent with no data-engineering surface, next to the data layer it calls: dbt, lineage, and cost.
- [Altimate AI vs Databricks Genie Code](https://altimate.ai/comparisons/altimate-vs-databricks-genie-code.md): Altimate AI vs Databricks Genie Code: public ADE-Bench proof vs internal benchmarks, over a dozen data platforms vs workspace-only, and BYO LLM.
- [Altimate AI vs dbt Wizard](https://altimate.ai/comparisons/altimate-vs-dbt-wizard.md): Altimate AI vs dbt Wizard on the public ADE-Bench leaderboard, 78% vs 59%, plus GA status, VS Code support, BYO LLM, and the warehouse cost layer dbt lacks.
- [Altimate AI vs Espresso AI](https://altimate.ai/comparisons/altimate-vs-espresso-ai.md): Altimate AI vs Espresso AI: prevention in development, team collaboration on savings, and metadata-driven optimization that never sits in the query path.
- [Altimate AI vs Keebo](https://altimate.ai/comparisons/altimate-vs-keebo.md): Altimate AI vs Keebo: SLA-safe autonomous optimization vs aggressive warehouse shutdowns, full-stack coverage beyond warehouses, and dev-time prevention.
- [Altimate AI vs Revefi](https://altimate.ai/comparisons/altimate-vs-revefi.md): Altimate AI vs Revefi: continuous autonomous tuning with auto-revert guardrails, deterministic AST-based SQL rewrites, and dbt-repo fixes before merge.
- [Altimate AI vs Seemore Data](https://altimate.ai/comparisons/altimate-vs-seemore-data.md): Altimate AI vs Seemore Data: prevention in development, multi-cloud beyond Snowflake, an AI Studio, and automated query tagging for team chargebacks.
- [Altimate AI vs SELECT (select.dev)](https://altimate.ai/comparisons/altimate-vs-select-dev.md): Altimate AI vs SELECT for Snowflake cost optimization: autonomous intraday warehouse sizing, IDE prevention, Altimate Studio, spend forecasting, and pricing.
- [Altimate AI vs Snowflake Cortex Code](https://altimate.ai/comparisons/altimate-vs-snowflake-cortex.md): Altimate AI vs Snowflake Cortex Code (now CoCo) on the public ADE-Bench leaderboard, 78% vs 65%, plus warehouse coverage, BYO LLM, and deterministic guardrails.

## Skills

- [Skills & Tools](https://altimate.ai/skills.md): Altimate Code gives your AI agent purpose-built tools for SQL, dbt, lineage, testing, and warehouse work. Skills are the workflows it runs.
- [Altimate Setup](https://altimate.ai/skills/altimate-setup.md): Connect Altimate Code to your warehouse and dbt project before the first task. The skill walks you through credentials and checks that the agent can reach them.
- [Cost Report](https://altimate.ai/skills/cost-report.md): Find where Snowflake spend is leaking. Altimate Code analyzes query costs, ranks top spenders, and recommends warehouse tuning and query fixes.
- [Data Parity](https://altimate.ai/skills/data-parity.md): Compare two tables or query results after a migration or refactor. Altimate Code reports row count, schema, key, and value differences as sign-off evidence.
- [Data Viz](https://altimate.ai/skills/data-viz.md): Build charts, dashboards, and interactive views straight from your query results, so you can spot trends and share findings without leaving your editor.
- [dbt Analyze](https://altimate.ai/skills/dbt-analyze.md): Analyze the blast radius of dbt model changes using dependency information and column-level lineage.
- [dbt Develop](https://altimate.ai/skills/dbt-develop.md): Build dbt models that fit your project structure: correct layers, naming conventions, refs, sources, YAML, and validation. Not just SQL generation.
- [dbt Docs](https://altimate.ai/skills/dbt-docs.md): Write dbt model and column descriptions that explain meaning, not just names. Altimate Code reads model SQL and drafts docs that are actually useful.
- [dbt Test](https://altimate.ai/skills/dbt-test.md): Add schema tests, unit tests, and data quality checks that match model risk. Altimate Code inspects columns and relationships and suggests the right tests.
- [dbt Troubleshoot](https://altimate.ai/skills/dbt-troubleshoot.md): Diagnose dbt compilation failures, runtime errors, failing tests, wrong results, and performance issues.
- [dbt Unit Tests](https://altimate.ai/skills/dbt-unit-tests.md): Generate dbt unit test YAML from your model logic. Altimate Code reads joins, CASE statements, and null handling, then writes mock inputs and expected outputs.
- [Lineage Diff](https://altimate.ai/skills/lineage-diff.md): Compare column-level lineage between two SQL versions to see how data flow changed, not just which lines changed. Built for dbt model reviews.
- [PII Audit](https://altimate.ai/skills/pii-audit.md): Classify schema columns for PII and check whether SQL or dbt models expose sensitive data before it reaches production or external consumers.
- [Query Optimize](https://altimate.ai/skills/query-optimize.md): Find the SQL anti-patterns that make a query slow or expensive, such as SELECT * and missing partition pruning, and get a rewrite with the reason for each fix.
- [Schema Migration](https://altimate.ai/skills/schema-migration.md): Compare old and new schema definitions before you run a DDL migration. Altimate Code flags dropped columns, type narrowing, and changes that break consumers.
- [SQL Review](https://altimate.ai/skills/sql-review.md): Catch SQL anti-patterns, performance risks, and safety problems before code ships. Altimate Code grades queries and explains every finding with a fix.
- [SQL Translate](https://altimate.ai/skills/sql-translate.md): Convert SQL between Snowflake, BigQuery, Postgres, MySQL, Databricks, Redshift, DuckDB, and other dialects.
- [Teach](https://altimate.ai/skills/teach.md): Show Altimate Code one good example file. It extracts the reusable pattern, asks you to confirm, and saves the pattern as training for future sessions.
- [Train](https://altimate.ai/skills/train.md): Load your style guides, review checklists, glossary docs, and standards so the AI can apply them consistently.
- [Training Status](https://altimate.ai/skills/training-status.md): List what Altimate Code has learned about your project, grouped into patterns, rules, glossary terms, and standards, so you can review or remove stale entries.

## Integrations

- [Integrations](https://altimate.ai/integrations.md): altimate-code works with your entire data stack — warehouses, orchestrators, collaboration tools, and any LLM provider.

## Demos & Walkthroughs

- [Video Demos](https://altimate.ai/demos-walkthroughs.md): Watch Altimate Code in action. Demos and walkthroughs covering dbt documentation, testing, SQL peer review, PII masking, Airflow debugging, and more.
- [AI Agent Peer Review for dbt SQL](https://altimate.ai/demos-walkthroughs/ai-sql-peer-review-dbt.md): One prompt drives the full peer review. Seven mart models come out graded, fixed, and re-validated without a senior engineer in the loop.
- [Get Productive on a New Data Team with AI](https://altimate.ai/demos-walkthroughs/airflow-dag-context-aware-coding.md): Starting from a new codebase with zero familiarity, one prompt added a fifth Airflow DAG that matched the team's patterns perfectly.
- [Add Airflow DAGs That Match Your Project](https://altimate.ai/demos-walkthroughs/airflow-dag-pattern-matching.md): One prompt added a new DAG to an existing Airflow + DuckDB project. It read the codebase, matched the patterns, and ran clean on the first try.
- [dbt Column Rename: Check the Blast Radius](https://altimate.ai/demos-walkthroughs/dbt-column-rename-blast-radius.md): Renaming total_cents to gross_revenue_cents sounded like a one-line change. Blast radius analysis showed it touched models, metrics, YAML docs, and dashboards.
- [AI Agent dbt PR Review: Column Lineage](https://altimate.ai/demos-walkthroughs/dbt-pr-review-column-lineage.md): The code looked reasonable. Column-level lineage revealed 4 breaking downstream changes before merge.
- [Fix a Broken Airflow Pipeline with AI](https://altimate.ai/demos-walkthroughs/fix-broken-airflow-pipeline.md): One AI session traced, diagnosed, and fixed a failing e-commerce ETL pipeline with 5 broken dbt models.
- [Building dbt Docs with an AI Agent](https://altimate.ai/demos-walkthroughs/generate-dbt-documentation-ai.md): The project had 50% model coverage and 20% column coverage. The AI rewrote all of it in 17 minutes for $1.
- [Building dbt Tests with an AI Agent](https://altimate.ai/demos-walkthroughs/generate-dbt-tests-ai-agent.md): The project went from 24 tests to 53 in one session. The agent wrote 30 new tests, ran them, and confirmed all passing, for $1.51 total.
- [Masking PII with an AI Agent](https://altimate.ai/demos-walkthroughs/masking-pii-ai-agent-dbt.md): Most teams don't know where their PII lives. An AI agent found it, masked it, and validated everything, all for $3.
- [Get Productive Fast on a New Data Project](https://altimate.ai/demos-walkthroughs/new-data-project-zero-context.md): A product manager needs data in 20 minutes from a dbt project you never opened. Altimate Code reads the project, maps lineage, and writes the query.
- [Snowflake AI Services Cost Breakdown](https://altimate.ai/demos-walkthroughs/snowflake-ai-services-cost-breakdown.md): Your AI Services bill shows one number. This breaks it down by service type, model, user, and team — so you can answer when the CFO asks why costs spiked 40%.
- [5 Hidden Snowflake Cost Leaks Only AI Can Find](https://altimate.ai/demos-walkthroughs/snowflake-cost-leaks-ai.md): Five cost savings opportunities Snowflake's native tools won't surface — and how they added up to 32% off the bill.
- [Migrate SQL Server to Snowflake with dbt](https://altimate.ai/demos-walkthroughs/sql-server-snowflake-dbt-migration.md): Stored procedure logic in, validated dbt models out — with row count checks, schema diffs, and a migration dashboard stakeholders can actually trust.
- [SQL Server to Snowflake Migration with dbt](https://altimate.ai/demos-walkthroughs/sql-server-snowflake-migration-dbt.md): Altimate Code migrated SQL Server stored procedures to dbt on Snowflake, validated the output with data diff, and generated a dashboard to prove it worked.

## Blog

- [Blog](https://altimate.ai/blog.md): Insights on AI agents, agentic data engineering, Snowflake, Databricks, and analytics engineering from the Altimate AI team.
- [4 Blind Spots of Coding Agents in Data Engineering](https://altimate.ai/blog/4-blind-spots-of-general-coding-agents-in-data-engineering.md): Discover where general coding agents like Claude fail at data engineering—schema hallucination, cross-warehouse gaps, and more.
- [Adaptive Compute vs. Altimate AI Auto Tune Optimization](https://altimate.ai/blog/adaptive-compute-vs-auto-tune-a-practical-guide-to-optimizing-snowflake-warehouses.md): Optimize Snowflake warehouses with Adaptive Compute and Altimate Auto Tune solutions. Learn their functionalities, tradeoffs, and decide based on your needs
- [Snowflake Adaptive Compute vs Auto-Tune After GA](https://altimate.ai/blog/adaptive-compute-vs-auto-tune-optimizing-snowflake-warehouses.md): Snowflake Adaptive Compute is now GA. See what a Snowflake adaptive warehouse changes in parameters and per-query billing, and what auto-tuning still does.
- [Altimate Code vs Claude Code vs Cursor Compared](https://altimate.ai/blog/altimate-code-vs-claude-code-vs-cursor.md): Altimate Code vs Claude Code vs Cursor vs Cortex Code CLI. What each agent does for a data team, what it costs, and which one fits your stack.
- [Snowflake AI Cost Optimization With Warehouse Auto-Tuning](https://altimate.ai/blog/altimate-lite-autonomous-agents-for-snowflake-cost-optimization.md): Altimate Lite automates Snowflake warehouse auto-tuning for AI cost optimization. Free 21-day trial, ~19% average savings, no performance impact.
- [9 Agentic Data Engineering Tools for VS Code](https://altimate.ai/blog/best-agentic-data-engineering-tools-vs-code.md): Nine agentic data engineering tools for VS Code, scored on warehouse context, dbt awareness, cost visibility and license, with where each one stops.
- [Best Data Conferences 2026: Dates, Venues, Who Should Go](https://altimate.ai/blog/best-data-conferences-2026-the-complete-guide.md): Dates, venues and attendance for 7 data conferences in 2026, from Snowflake Summit to dbt Summit, with picks for data engineers and data leaders.
- [10 Best MCP Servers for Data Engineering](https://altimate.ai/blog/best-mcp-servers-for-data-engineers.md): MCP lets an agent look things up instead of guessing. Ten best MCP servers for data engineering, what each exposes, and the security question first.
- [Databricks Pricing Calculator and 6 Levers That Cut Cost](https://altimate.ai/blog/beyond-the-databricks-cost-calculator-6-levers-that-actually-cut-your-bill.md): The Databricks pricing calculator multiplies the DBU rate by your hours. Six levers it leaves out, from auto termination to Photon, set what you pay.
- [Blast Radius Analysis for dbt with Altimate Code](https://altimate.ai/blog/blast-radius-analysis-using-altimate-code.md): Altimate Code maps the full blast radius of a dbt column rename, catching breaking changes across SQL, YAML, and semantic layers before you push.
- [How AI Agents Can Optimize Dynamic Table Spend](https://altimate.ai/blog/can-ai-agents-reduce-the-cost-of-snowflake-dynamic-tables.md): Understand the surprising cost implications of Snowflake Dynamic Tables and how AI Agents can help to massively optimize Snowflake spend
- [Claude Code vs. Altimate Code for Data Engineering](https://altimate.ai/blog/claude-code-or-altimate-code-for-data-engineering.md): An analysis of the performance of Claude Code vs. the open source Altimate Code agentic harness for data engineering tasks.
- [8 Column-Level Lineage Use Cases for Data Teams](https://altimate.ai/blog/column-level-lineage-use-cases.md): Eight column-level lineage use cases where knowing which field, not just which table, changes the work rather than the reporting.
- [Cost per Task vs Dollars per Million Tokens for AI Agents](https://altimate.ai/blog/cost-per-task-vs-dollars-per-million-tokens.md): Cost per task divides all agent spend, failed runs included, by the tasks that pass your rule. A method, a formula and worked numbers for data engineering.
- [Can AI Manage Snowflake Credits Automatically?](https://altimate.ai/blog/could-ai-teammates-be-the-secret-to-efficient-snowflake-cost-management.md): How AI teammates manage Snowflake credits: tune queries, size virtual warehouses, set cluster keys and send cost alerts beside a human admin.
- [Databricks All-Purpose vs Jobs Compute Cost](https://altimate.ai/blog/databricks-all-purpose-vs-jobs-compute.md): Scheduled jobs left on all-purpose compute pay for idle time and hide their cost. Compare all-purpose vs Jobs compute and find the jobs to move.
- [Databricks Cluster Cost Beyond the DBU Bill](https://altimate.ai/blog/databricks-cluster-cost-beyond-dbu-bill.md): Databricks cluster cost has two bills, DBUs and cloud VMs. On job clusters, infra ran 3.7x the DBU cost. How to measure both and check your own split.
- [Databricks FinOps: Chargeback and Attribution](https://altimate.ai/blog/databricks-finops-chargeback-cost-attribution.md): A Databricks FinOps guide to cost attribution and chargeback: how tags attribute spend, three SQL queries to measure coverage, and the gaps no tag reaches.
- [Databricks Model Serving and Vector Search Costs](https://altimate.ai/blog/databricks-model-serving-cost-idle-vector-search.md): Databricks Model Serving cost keeps running after a project ends, through idle endpoints and orphaned Vector Search. What we found, and a 5-minute check.
- [What Databricks Predictive Optimization Costs](https://altimate.ai/blog/databricks-predictive-optimization.md): Databricks Predictive Optimization runs OPTIMIZE, VACUUM and ANALYZE on Unity Catalog managed tables. See which tables it covers and how to find what it costs.
- [Databricks Autoscaling vs Right-Sizing Costs](https://altimate.ai/blog/databricks-right-sizing-vs-autoscaling.md): Databricks autoscaling from 1 to 4 workers cost 75% more than 4 fixed workers in this test. How to choose between autoscaling and right-sizing.
- [Databricks Semantic Layer and Genie Ontology](https://altimate.ai/blog/databricks-semantic-layer-genie-ontology.md): The Databricks semantic layer pairs modeled Unity Catalog semantics with context Genie infers from usage, ranked by authority and gated by permissions.
- [Databricks Serverless vs Classic Compute Cost](https://altimate.ai/blog/databricks-serverless-vs-classic-compute-which-one-is-actually-cheaper.md): Serverless costs more per DBU but avoids idle time. Benchmarks show a 30-minute break-even point for picking the cheaper Databricks compute option.
- [Databricks Streaming Tables: Always-On Costs](https://altimate.ai/blog/databricks-streaming-tables-continuous-vs-triggered.md): Databricks streaming tables stay incremental in triggered mode. What continuous execution costs in DBUs, and how to pick the cheapest mode that meets freshness.
- [7 dbt Anti-Patterns to Catch Before Merge](https://altimate.ai/blog/dbt-anti-patterns-ai-should-catch.md): Seven dbt anti-patterns that pass review and cost you later, why each one survives a human read, and the dbt AI check that catches it before merge.
- [6-Step dbt Migration Playbook With an AI Agent](https://altimate.ai/blog/dbt-migration-with-an-ai-agent-playbook.md): A six-step playbook for dbt migration with an AI agent. It treats business-logic parity as the deliverable and proves it with data migration testing.
- [DeepSeek vs Claude Sonnet: AI Agent Cost, Speed & Accuracy](https://altimate.ai/blog/deepseek-vs-claude-sonnet-ai-agent-benchmark.md): We ran 540 trials comparing DeepSeek v4 Pro vs Claude Sonnet 4.6 in a data agent. Cost was just the start — the trace tells a very different story.
- [Deterministic Tooling for AI Agents vs LLM-Only](https://altimate.ai/blog/deterministic-tooling-vs-llm-only-data-agents.md): Some questions about your data have exact answers. Five reasons deterministic tooling for AI agents beats a model on those, and where the model still wins.
- [Cut dbt Development Time by 20% with Power User for dbt](https://altimate.ai/blog/how-i-cut-dbt-development-time-by-20-with-the-power-user-vscode-extension.md): Power User for dbt extension in VSCode cuts dbt development time by 20% through expert skills and AI-driven documentation automation
- [How I Stopped Running dbt Compile 50 Times a Day](https://altimate.ai/blog/how-i-stopped-running-dbt-compile-50-times-a-day.md): dbt compile renders Jinja into SQL and writes it to target/. How I moved the edit, compile and check loop into a dbt VS Code extension, feature by feature.
- [Databricks System Tables Cost Queries](https://altimate.ai/blog/how-to-find-out-what-databricks-is-costing-you-with-system-tables.md): Databricks system tables hold usage, not cost. SQL queries that price usage and trace it to the workspace, job, failed run, team and identity behind it.
- [Altimate Code: the agentic harness for data engineering](https://altimate.ai/blog/introducing-altimate-code.md): Altimate code is an agentic harness for data engineering. It outperforms other AI solutions on data tasks based on common benchmarks.
- [Optimize Snowflake Queries: Strategies for Data Engineers](https://altimate.ai/blog/optimizing-snowflake-queries-expert-strategies-for-data-engineers-and-analysts.md): Unlock the secrets to turbocharging your Snowflake queries with our expert guide. Discover tips and best practices tailored for data engineers & analysts
- [Debug Slow dbt Models: Power User for dbt's Query Profiler](https://altimate.ai/blog/power-user-for-dbt-can-now-tell-you-why-your-model-is-slow.md): New in Power User for dbt: one-click query profiling reads Snowflake, BigQuery, Postgres, and Databricks execution plans to explain why your dbt model is slow.
- [How to Review AI-Generated dbt Code](https://altimate.ai/blog/review-ai-generated-dbt-code-before-production.md): AI-written dbt models compile and pass data tests while hiding bugs. Five failure modes, why the usual checks miss them, and a review to run before you merge.
- [Right-sizing Databricks Job Clusters](https://altimate.ai/blog/right-sizing-databricks-job-clusters-automatically.md): Auto Tune learns from each Databricks job’s runs, right-sizes its cluster inside the bounds you set, and reverts if a run regresses. Median job 33% cheaper.
- [How Deterministic Tools Cut LLM Spend on dbt Changes](https://altimate.ai/blog/schema-validation-costs-0-tokens-how-deterministic-tools-cut-llm-spend.md): Schema validation, lineage and lint can run as compiled code with no model call. See how deterministic tools cut LLM spend on one dbt change, and what remains.
- [9 Signs You Need an Agent-First Data Platform](https://altimate.ai/blog/signs-data-platform-needs-agent-first-overhaul.md): Most AI agent pilots stall on the platform underneath them, not the model. Nine diagnostics for whether you need an agent-first data platform.
- [Snowflake Cortex Pricing and Spend Caps](https://altimate.ai/blog/snowflake-cortex-pricing-spend-caps.md): Snowflake Cortex pricing per service, by token, message, page and GB indexed. Which Cortex AI services you can cap, the 8-hour lag, and how to track the rest.
- [12 Snowflake Cost Optimization Techniques for 2026](https://altimate.ai/blog/snowflake-cost-optimization-techniques.md): Twelve Snowflake cost optimization techniques that cut Snowflake compute cost, ranked from free config changes to continuous tuning.
- [Snowflake Interactive Warehouse Cost](https://altimate.ai/blog/snowflake-interactive-warehouses-cheaper-per-hour-not-always-cheaper.md): Snowflake interactive warehouse pricing, the break-even against Gen1 and Gen2, the 5-second query cap and fallback cost, and how to pilot one safely.
- [Power User for dbt's Embedded MCP Server for Cursor](https://altimate.ai/blog/supercharging-cursor-ide-how-the-dbt-power-user-extensions-embedded-mcp-server-unlocks-ai-driven-dbt-development.md): Power User for dbt runs an embedded MCP server in VS Code, so the AI assistant in Cursor can query your dbt schema, compile models, and run tests.
- [Claude Code for Data Engineering With Altimate Skills](https://altimate.ai/blog/teaching-claude-code-the-art-of-data-engineering-introducing-altimate-skills.md): Use Claude Code for data engineering with Altimate Skills, open-source skills that add dbt and Snowflake workflows and project context.
- [Claude Code Cost for Data Teams and How to Cut It](https://altimate.ai/blog/the-2000-month-claude-bill-your-data-team-doesnt-need.md): Claude Code cost for a data team reaches $2,000 a month at Anthropic's published averages. See the arithmetic and five levers that cut tokens on dbt work.
- [Deterministic Validation Outside the LLM Loop](https://altimate.ai/blog/the-correctness-layer-deterministic-validation-outside-the-llm-loop.md): Deterministic validation checks a data agent's work showing outcomes, how the loop ends, and the CI job.
- [The Correctness Layer: Why Data Agents Need Determinism](https://altimate.ai/blog/the-correctness-layer-in-ade.md): How Altimate's data agent tops benchmarks by keeping LLMs out of SQL validation, lineage, and diffs with a deterministic Rust correctness layer.
- [LLM Token Inflation: Why Your AI Bill Keeps Growing](https://altimate.ai/blog/the-great-token-heist-of-26.md): Token counts aren't standard across AI vendors. Learn how tokenizer changes, hidden fees, and currency gaps inflate your real LLM costs.
- [AI Token Costs and Why Your AI Coding Tool Bill Lies](https://altimate.ai/blog/the-hidden-cost-of-ai-coding-tools-why-your-token-bill-lies.md): The cost of AI coding tools depends on tokens per finished task. See how context re-reads, cache writes, thinking and retries grow your AI token costs.
- [Databricks DBU Cost and How Databricks Pricing Adds Up](https://altimate.ai/blog/understanding-databricks-compute-costs.md): How Databricks compute costs actually work: DBUs vs. cloud infrastructure, serverless vs. classic, and the system tables that show where the money goes.
- [Claude Code SQL and dbt Skills for Data Teams](https://altimate.ai/blog/we-created-data-engineering-skills-for-claude-code.md): Claude Code skills for SQL and dbt. Review and optimize SQL, build and test dbt models, compare data outputs, audit PII and read warehouse cost.
- [AI Agents in Data Engineering: Guardrails & Validation](https://altimate.ai/blog/what-ai-agents-are-really-changing-in-data-engineering.md): How AI agents for data engineering change hiring, output validation with data diffs, and governance, from Altimate AI's Pradnesh Patil.
- [Where AI Agents Belong in Data Engineering](https://altimate.ai/blog/where-ai-agents-belong-in-data-engineering-the-correctness-layer.md): Why a deterministic correctness layer is essential for production-grade pipelines: a practical blast-radius analysis example with Altimate Code.
- [Why AI Agents Break in Production: The Missing Harness](https://altimate.ai/blog/why-ai-agents-break-in-production-the-missing-harness-in-your-data-stack.md): AI agents write wrong SQL joins and query tables that do not exist. Pradnesh Patil explains the AI agent governance harness that stops both.
- [7 Ways AI Agents in Production Fail on Data Stacks](https://altimate.ai/blog/why-ai-agents-fail-on-production-data-stacks.md): AI agents fail on production data stacks in ways a dev sandbox hides. Seven failures, from inherited role grants to backfills, and the control that stops each.
- [10 Reasons AI Coding Agents Fail at Data Engineering](https://altimate.ai/blog/why-ai-coding-agents-fail-at-data-engineering.md): AI coding agents fail at data engineering for one structural reason. Ten specific failure modes, why each one happens, and the fix that holds.
- [Why Your Snowflake Bill Grows 30% a Quarter](https://altimate.ai/blog/why-your-snowflake-bill-grows-by-30-percent-a-quarter.md): A Snowflake bill that grows 30% a quarter nearly triples in a year. Six drivers behind that growth, each with the ACCOUNT_USAGE query that finds it.
- [Streamlining Data Documentation: Generative AI Best Practices](https://altimate.ai/blog/write-better-data-docs-faster.md): Discover best practices for writing effective data documentation and learn how Gen AI tools can streamline the process, reducing errors and saving time
- [You Are the Trust Layer: Managing AI Agents at Scale](https://altimate.ai/blog/you-are-the-trust-layer-managing-data-engineering-ai-agents-at-scale.md): AI writes the code, but you approve it. Learn why developers are now trust layers for AI agents—and why that's becoming unsustainable.

## Guides

- [The AI-Ready Data Engineer](https://altimate.ai/ai-guide.md): A practical guide for data engineers adopting AI — covering core concepts, infrastructure decisions, and hands-on strategies to build AI-ready data platforms.
- [Chapter 2: The 48-Hour Crash Course](https://altimate.ai/ai-guide/48-hour-crash-course.md): Learn AI essentials in a weekend. Build your first RAG app and get to grips with LLMs, prompt engineering, AI agents, vector databases, and MCP.
- [Closing thoughts](https://altimate.ai/ai-guide/final-thoughts.md): Where to start, what to build in the first week, and the infrastructure question your team will be answering by 2027.
- [Chapter 3: The One-Month Program](https://altimate.ai/ai-guide/one-month-program.md): Build production AI skills in four weeks: advanced RAG, multi-agent frameworks with LangGraph and CrewAI, LLMOps, and fine-tuning with LoRA and QLoRA.
- [Chapter 5: Resources and Milestones](https://altimate.ai/ai-guide/resources.md): Curated AI resources for data engineers: top courses from DeepLearning.AI and Fast.ai, essential GitHub repos, YouTube channels, communities, and docs.
- [Chapter 4: The Three-Month Advanced Track](https://altimate.ai/ai-guide/three-month-advanced-track.md): For the ambitious data engineer. Cover research papers, multimodal systems, deployment patterns, evaluation frameworks, and reasoning models like DeepSeek-R1.
- [Chapter 1: Why AI Matters for Data Engineers](https://altimate.ai/ai-guide/why-ai-matters.md): Data engineering is becoming the foundational layer every AI initiative depends on. Understand the shift from executor to orchestrator, and why it matters now.

## Company

- [About Altimate AI: Founders, Team and Investors](https://altimate.ai/company.md): Altimate AI builds autonomous agents that can be trusted with production data. Meet the co-founders, the team, and the investors and advisors.

## Pricing

- [Altimate Pricing: Free Plan and Pro at $29/Seat](https://altimate.ai/pricing.md): Start free with 10 million tokens and no credit card. Pro is $29 per seat per month and includes 20 million tokens per seat.

## Customers

- [Customers](https://altimate.ai/customers.md): Enterprise data teams — Elastic, Booking.com, Carta, Coinbase, and 20+ more — run Altimate in production. 3× faster development. 10–15× faster migrations.

## Security

- [Security](https://altimate.ai/security.md): Altimate AI is built security-first. Metadata only, never your data. SOC 2 Type II certified, multi-tenant isolated, encrypted in transit and at rest.

## Changelog

- [Changelog](https://altimate.ai/changelog.md): Every shipped update to the Altimate platform: dbt Power User, Altimate Code, Datamates, and cost intelligence for Snowflake and Databricks.

## Other

- [Altimate on Snowflake](https://altimate.ai/altimate-on-snowflake.md): Discover how Altimate helps you manage your Snowflake instances with AI-powered cost optimization, query analysis, and autonomous operations.
- [Brand Kit](https://altimate.ai/brand.md): Download official Altimate AI logos, including icon-only and white versions, with the brand colors and the rules for placing and linking the logo.
- [Privacy Policy](https://altimate.ai/privacy.md): Read the Altimate AI privacy policy: what personal data we collect, how we use, keep, and share it, and your rights under GDPR and the CCPA/CPRA.
- [Product Highlights](https://altimate.ai/product-highlights.md): Real use cases for Altimate Code, the dbt Power User plugin, Altimate MCP, and the Enterprise platform. One page each, grounded in the help docs.
- [Auto Tune for Snowflake compute savings](https://altimate.ai/product-highlights/altimate-lite-snowflake-warehouse-cost.md): Altimate Lite is a Snowflake Native App that cuts warehouse cost in your own account. It copies nothing out. Turn Auto Tune on and idle time stops billing.
- [Read dbt lineage in VS Code with AI chat](https://altimate.ai/product-highlights/ask-ai-about-dbt-lineage-in-vs-code.md): Open the Lineage tab, pick a dbt model, and ask Altimate Code what it depends on, what depends on it and how any one column is calculated.
- [Enterprise Platform highlights](https://altimate.ai/product-highlights/category/enterprise-platform.md): Cost, performance, and governance across Snowflake and Databricks, plus Altimate Lite for Snowflake. Filter by platform in the tech stack.
- [dbt PowerUser Plugin highlights](https://altimate.ai/product-highlights/category/poweruser-plugin-for-dbt.md): Product highlights for dbt Power User, the VS Code extension with 1M+ installs. Column-level lineage, docs, tests, and query help for dbt projects.
- [Databricks cost breakdown by SKU, warehouse](https://altimate.ai/product-highlights/databricks-cost-breakdown-workspace-sku-cluster.md): A Databricks cost breakdown you can drill. Five categories on the Summary page, the SKU behind the largest, then the named warehouses that spend it.
- [dbt macros and ref() explained in VS Code](https://altimate.ai/product-highlights/dbt-macros-and-ref-explained-on-hover.md): Hover over a dbt macro or ref() in VS Code. See which models use the macro and how deep the model sits, then ask Altimate Code to explain it.
- [Debug a dbt model by profiling each CTE](https://altimate.ai/product-highlights/debug-a-dbt-model-by-profiling-each-cte.md): Debug a dbt model in one click. Profile CTEs shows the runtime and row count of every CTE, so the join that inflates your rows stands out.
- [dbt unit tests, written by AI in VS Code](https://altimate.ai/product-highlights/generate-dbt-unit-tests-in-the-documentation-editor.md): Click plus next to Unit Tests in the Documentation Editor and Altimate Code proposes dbt unit test scenarios with full YAML, added only after you approve.
- [Slow dbt query? Profile it in VS Code](https://altimate.ai/product-highlights/profile-a-slow-dbt-query-execution-plan.md): Profile a slow dbt query in one click. Altimate Code reviews the compiled SQL for correctness bugs, anti-patterns and cost, then ranks the fixes.
- [Where your Snowflake AI credits actually go](https://altimate.ai/product-highlights/snowflake-cortex-ai-cost-breakdown.md): Altimate Lite gives you a Snowflake Cortex AI cost breakdown by service, user, and model, then drills into single calls. Usage data never leaves the account.
- [Snowflake cost attribution by ownership rule](https://altimate.ai/product-highlights/snowflake-cost-alerts-by-team.md): Attribute Snowflake cost to the team level. Assign spend by warehouse or by query, then show each team's share and highlight any orphaned spend.
- [Studio answers cost questions with citations](https://altimate.ai/product-highlights/snowflake-cost-analysis-ai-cited-answers.md): Snowflake cost analysis in plain English. Ask Studio about spend across AI Services, Serverless and warehouses, and every number traces to its source.
- [Spot the run where a query got expensive](https://altimate.ai/product-highlights/snowflake-query-cost-over-time.md): Track one Snowflake query's cost over time. Every run sits under one row, so you see which run started costing more and what the platform found wrong.
- [Snowflake Auto Tune modes and safe backoff](https://altimate.ai/product-highlights/snowflake-warehouse-auto-tune-right-sizing.md): Altimate Auto Tune right-sizes and suspends Snowflake warehouses automatically, and reverts to the default size if queue time or latency crosses a threshold.
- [Compare two workload runs to find the cause](https://altimate.ai/product-highlights/snowflake-workload-root-cause-analysis.md): Compare two runs of a dbt, Tableau, or Snowflake workload and get the root cause named. The warehouse, the task count, or the code.
- [Support](https://altimate.ai/support.md): Get help with Altimate AI products. Contact our support team for issues, feature requests, or questions about Altimate MCP and Power User for dbt.
- [Terms & Conditions](https://altimate.ai/terms.md): Read the terms and conditions for Altimate AI products. They cover orders, subscriptions, billing, refunds, free trials, user accounts, and content rules.
- [Tutorials](https://altimate.ai/videos.md): Watch tutorials and video guides for Altimate AI products. Explore popular use cases to accelerate your data engineering and dbt development.

## Elsewhere

- [Altimate documentation](https://help.altimate.ai/llms.txt): full product documentation, separately indexed
- [Altimate Code (GitHub)](https://github.com/AltimateAI/altimate-code): the open-source agentic data engineering harness
- [Power User for dbt (GitHub)](https://github.com/AltimateAI/vscode-dbt-power-user): source for the VS Code extension
- [Power User for dbt (VS Code Marketplace)](https://marketplace.visualstudio.com/items?itemName=innoverio.vscode-dbt-power-user): install the extension
- [DataPilot CLI (GitHub)](https://github.com/AltimateAI/datapilot-cli): command-line interface
- [Altimate Code docs](https://docs.altimate.sh/): harness documentation
- [YouTube](https://www.youtube.com/@altimateai): demos and walkthroughs
- [Careers](https://jobs.ashbyhq.com/altimate): open roles

## About

- Licence: CC-BY-4.0
- Contact: info@altimate.ai
- Privacy policy: https://altimate.ai/privacy