Every engagement is scoped narrowly and measured against a baseline, not against how good the demo looks.
AI Readiness & Strategy Audit
A clear-eyed assessment of where AI can actually move the needle in your product or operations, and where it's a distraction.
- •Audit of existing workflows, data, and infrastructure for AI fit
- •Prioritized opportunity map, ranked by effort vs. impact
- •Honest recommendation on build vs. buy vs. skip
- •Written report plus a working session with your team
Fixed-scope, 1–2 weeks
RAG & Knowledge System Design
Retrieval-augmented systems that answer questions grounded in your actual documents, with citations you can trust.
- •Chunking, embedding, and retrieval architecture tailored to your content
- •Evaluation harness with labeled queries, not vibes-based testing
- •Citation tracing so every answer can be checked against its source
- •Handoff docs so your team can extend it without me
Project-based, 4–8 weeks
LLM Application Engineering
Production-grade engineering around the model (guardrails, observability, fallbacks), not just a prompt in a text box.
- •Prompt and output evaluation pipelines wired into CI
- •Guardrails for cost, latency, and failure modes
- •Structured logging and tracing for every model call
- •Incremental rollout plan with kill switches
Embedded, 1–3 months
Agentic Workflow & Automation Design
Multi-step agents and tool-use workflows scoped tightly enough to be reliable, with humans in the loop where it matters.
- •Task decomposition and tool interfaces designed for reliability
- •Explicit escalation paths for anything outside the agent's confidence
- •Cost and latency budgets set before a single line of orchestration code
- •Post-launch monitoring for silent failure modes
Project-based, 4–10 weeks
Model Evaluation & Fine-Tuning
Rigorous benchmarking against your own data, and fine-tuning only when it actually beats a well-prompted base model.
- •Custom eval sets built from real production examples
- •Baseline comparisons before any fine-tuning is attempted
- •Fine-tuning and benchmarking against the baseline you started with
- •Ongoing regression suite to catch drift after launch
Project-based, 3–6 weeks
Team Enablement & Embedded Advisory
Hands-on pairing with your engineers so the capability stays in-house after the engagement ends.
- •Pair-programming and design review with your existing team
- •Internal playbooks for prompting, evaluation, and deployment
- •Office hours for ongoing questions as you build
- •No permanent dependency on outside consultants by design
Retainer, ongoing
Not sure which of these fits?
Most engagements start with a short conversation, not a sales pitch. Tell me what you're working on.