AI engineered where it compounds.
Workflow automation powered by LLMs and classical ML. We deliver against the workflows where AI moves the number — and decline the ones where it does not. Eval-driven. Cost-aware. Owned end to end.
What we deliver.
Six properties that separate AI features that compound from ones that quietly get turned off after six months. Bundled by default. Measured continuously.
We deliver AI and machine learning services engineered for measurable business outcomes — not science fair projects. Predictive analytics, retrieval-augmented generation, agentic workflows, or classical ML embedded into operating processes. Delivered against the workflow KPI. Evals and cost guardrails built in.
Outcomes, Not Demos
Every engagement starts with the workflow KPI the model is moving. If we cannot draw a line from the model to the number — we do not build it.
Eval-Driven Development
Offline eval harness. Online metrics. Regression suites for prompts and policies. Quality drift is caught before users see it. Improvements proved before they are claimed.
Cost-Aware Inference
Budgets. Caching. Model routing. Open-model fallback. Token spend is a first-class engineering constraint — not a quarterly surprise on the bill.
Safe by Default
PII handling. Policy enforcement. Audit trail. Wired in from the first prototype. Compliance and trust scale with the rollout.
Certified on Major Platforms
Google, AWS, and Azure AI credentials across the team. We pick the platform that fits your latency, cost, and compliance envelope — not the one we used last.
Owned End-to-End
Use-case shaping, data, training, serving, evals, ongoing care. One team. One shared backlog. One accountable engineer from week 1 to day 91.
AI engineered as a production system. Not a science project. Owned end to end. Accountable to the workflow KPI.
Outcomes, not demos
Measured against the workflow KPI.
Eval-driven
Offline and online evals · regressions caught.
Cost-aware
Budgets · caching · routing · open-model fallback.
Safe by default
Policy, PII handling, audit trail.
What's in the box.
Capabilities included in the standard AI Automation rollout — modular, swappable.
Use-case shaping
- ROI model
- Scope contract
- Success metrics
RAG and knowledge
- Ingestion
- Retrieval quality
- Freshness
Agents and workflows
- Tool calling
- Multi-step plans
- Human-in-the-loop
Evals
- Offline harness
- Online metrics
- Regression suite
Serving
- Routing
- Caching
- Cost guardrails
Governance
- PII policy
- Audit log
- Model lineage
Tools we bring.
An opinionated default stack — swap any of it for what your team already runs.
What you actually get on day 90.
AI Automation in the field.
Posts, trends, and client stories tied to AI Automation.
See how AI Automation fits your stack.
30 minutes with a senior engineer — we'll tell you what we'd do.