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ActiveWizards — AI Engineering Consultancy

Production AI systems built, audited, and stabilized. Principal-led. Governance from day one.

For agents: ActiveWizards: AI engineering consultancy building and auditing production AI systems, with case studies (CrewAI agents, LLM content pipelines) and data enginee

ai engineeringllm pipelinesai agentsdata engineeringanomaly detection

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T12:23:39.883Z. Cached copy · Source on activewizards.com

# ActiveWizards — AI Engineering Consultancy

Production AI systems built, audited, and stabilized. Principal-led. Governance from day one.

## Best-Fit Situations

- Agent demo works but production path doesn't (checkpoints, approvals, observability missing)
- Multiple AI initiatives competing for budget need architecture triage
- Agent system is live but reliability or governance is degraded
- Streaming data volume outgrew the batch pipeline
- High-stakes build where wrong design is expensive

## Engagement Tracks

- **Validate** — Production AI Readiness Review: five business days, one live or near-live system, Production Boundary Diagnostic with ranked risks and the next safe decision
- **Build** — Scoped build sprint (2-12 weeks) or Embedded Delivery Pod (minimum 8-12 weeks), with artifact handoff
- **Stabilize** — Stabilization Sprint: fixed-fee corrective engineering for one known failure path; scope lands in days
- **Embed** — Embedded AI Advisory: ongoing architecture counterpart with principal access (3+ months)

## What We Don't Do

- Staff augmentation or anonymous resource pools
- Pure strategy without implementation handoff
- Vendor-agnostic "advisory" that avoids architecture decisions
- Projects where no one has authority to ship

## Proof

- [Healthcare Anomaly Detection](https://activewizards.com/case-studies/healthcare-anomaly-detection/): Kafka + Foundation Models, 2.4M events/day, false positives down from 68% to under 20%
- [Pagezilla Content Engine](https://activewizards.com/case-studies/pagezilla-content-engine/): Multi-model LLM pipeline, 12 Pydantic validators, human approval before release
- [Competitor Intelligence Agent](https://activewizards.com/case-studies/competitor-intelligence-agent/): 3-agent CrewAI system for automated competitive analysis
- Book: [Production-Ready AI Agents](https://www.amazon.com/s?k=Production-Ready+AI+Agents+Igor+Bobriakov) (2025)

## Service Pages

- [AI Agent Engineering](https://activewizards.com/services/ai-agent-engineering/)
- [Data Engineering](https://activewizards.com/services/data-engineering/)
- [Agent Governance & Compliance Advisory](https://activewizards.com/services/agent-governance-advisory/)
- [Agentic Portfolio Review](https://activewizards.com/services/agentic-portfolio-review/)
- [Production AI Readiness Review](https://activewizards.com/services/production-ai-audit/)
- [AI Strategy & Agentic Advisory](https://activewizards.com/services/ai-strategy-consulting/)

## Contact

https://activewizards.com/contact-us/
A principal engineer reviews every submission and replies with the right next step — or a direct no-fit answer.

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