Services
Three ways to work together
Pick based on where you actually are — not where you wish you were.
AI/ML Strategy Workshop
For leadership teams — CTO, VP Data/AI, Head of Analytics — who need a prioritized AI/ML roadmap before committing budget, or who have competing ideas internally and no consensus on what to build first.
- A single 6-hour, on-site working session
- A use-case inventory and prioritization exercise
- A platform/tooling assessment across your existing stack
- A written roadmap with sequenced recommendations and rough cost/effort estimates
- A 30-minute follow-up call two weeks later
ML Operationalization
For teams with a data scientist’s model that works in a notebook but has never made it to production — or has, and breaks quietly.
- Production architecture design: model registry, CI/CD, monitoring, drift detection, retraining pipeline
- Implementation on your platform of choice — Snowpark ML, Databricks MLflow, or equivalent
- Documentation and hands-on training so your team owns it after handoff
AI Operationalization
For teams with a GenAI or agentic pilot — a chatbot, copilot, or text-to-SQL assistant — that works in a demo but isn’t trusted enough for real users or real decisions.
- Verified query and semantic layer design, so answers come from a governed source of truth
- Guardrails against prompt injection, hallucination, and unsafe outputs
- An observability and evaluation pipeline — tracing, drift monitoring, automated evals
- Governance documentation for security and compliance review
On publishing pricing
No Snowflake or Databricks consulting firm publishes pricing. That’s exactly why this page does — real numbers, including the hourly rate and hour count behind each total, not just a range. The right client — one with real budget — appreciates the transparency, and it filters out the wrong ones before either of us wastes a call.