Services

Practical AI delivery, end to end.

We tailor engagements for your team, timeline, and risk profile. Typical work spans discovery through production hardening and enablement.

AI strategy & roadmap

Define what “good” means, select high-return use cases, and create a roadmap your team can execute.

  • Use-case discovery workshops
  • Data readiness assessment
  • Security, privacy, and governance design
  • ROI model and KPI instrumentation plan

LLM applications (RAG & agents)

Build reliable LLM features with rigorous evaluation and guardrails.

  • Retrieval pipelines and relevance tuning
  • Tool use, function calling, and orchestration
  • Prompting patterns and safety mitigations
  • Offline/online evaluation harnesses

MLOps & platform

Turn prototypes into maintainable systems with visibility and controls.

  • CI/CD for models and prompts
  • Observability (quality, latency, drift)
  • Feature store + data quality patterns
  • Environment & access design (least privilege)

Enablement & training

Upskill teams so they can operate and extend what we build.

  • Architecture reviews and code walkthroughs
  • Playbooks for evaluation and incident response
  • Hands-on workshops for engineers and PMs
  • Executive briefings for stakeholder alignment

Flagship: AI Value Sprint (2–4 weeks)

A structured engagement to go from ambiguous ideas to a shippable pilot and rollout plan.

Week 1: Focus

Use-case selection, success metrics, and a thin-slice architecture.

Week 2: Build

Prototype with baseline evaluations, red-teaming, and system prompts.

Weeks 3–4: Harden

Monitoring, fallback strategies, and a delivery plan your team can own.

Want a recommendation?

We’ll suggest an engagement shape after a quick discovery call.