Do you work in our codebase or build separately?

Your codebase, your repo, your CI/CD. We push branches, you review them. By engagement end, your team owns the diff.

What model do you use?

Whatever clears your eval bar at acceptable cost and latency. We've shipped on Claude, GPT-4/5, Gemini, Llama, and combinations. Multi-provider routing is built in by default.

How do we know it works?

We don't ship without a regression-tested eval suite. You see the eval scores at every gate. If the eval bar drops on a model swap, the swap doesn't ship.

Can we extend it after you leave?

Yes — that's the point. The runbook documents every extension point, and the harness is yours. If you'd rather we keep operating it, the Managed AI Stack engagement covers that.

Agentic Automation

Production-grade agents and workflows on your stack — harness, orchestration, tools, MCP, and evals.

Scope this engagement Read how it works

SHAPE · Fixed fee · 6–10 weeks · 1 lead + 2–3 builders

Engineers wiring production-grade AI agents into a client tech stack with orchestration, tools, and a multi-step workflow trajectory.

THE PROBLEM

Demos run on happy paths. Production runs on the long tail. We build agents that survive the long tail — instrumented, evaluated, and rollback-able.

01HOW IT WORKS

The shape of the engagement.

01Harness

STEP 1

Pick the bones

Framework, framework-light, or framework-free. Decision driven by your platform team's tolerance for new abstractions, not vendor preference. We've shipped on LangGraph, custom orchestrators, and pure functions.

02Tools & MCP

STEP 2

Real tool routing

Skills registered, MCP servers integrated, tool sandboxing, and context preservation across multi-step workflows. Token-efficient prompts that survive a 200-step trajectory.

03Eval & ship

STEP 3

Eval-gated rollout

Golden sets, regression suites, and a rollback plan before go-live. We don't ship without an eval bar your CTO can read.

WHAT WALKS OUT THE DOOR

Production agentEval suiteRunbookCost & latency dashboardsRollback playbook

02ACROSS INDUSTRIES

How agentic automation applies in your industry.

SELECT SECTOR ↓

HOW IT APPLIES

Dispute triage, KYC refresh, credit memo drafting, and middle-office reconciliations. Audit logging and model-risk packaging are first-class citizens, not afterthoughts.

WHAT TRIPS PEOPLE UP

MRM will ask 'what changed' on every prompt update. Versioned prompts + diffable evals are non-negotiable.

EXPLORE INDUSTRY

ILLUSTRATIVE ENGAGEMENT

DISPUTES RESOLVED ≤24H

+47%

Tier-1 retail bank · 9-month live

03FAQ

What teams ask before signing.

04OFTEN PAIRED WITH

What usually comes next.

05IMPLEMENTATION

Implementation Services

End-to-end rollout — integrations, data plumbing, observability, validation harness, and rollback.

06RUN

Managed AI Stack

Two ways in, one way to run it forward. Bring us the AI stack you already ship, or have us build it — both paths converge on a single monthly retainer that owns uptime, drift, cost, and one new workflow each month. We run it forward, regardless of who shipped v1.

02SECURITY

AI Security & Governance

Threat modelling, data-loss prevention, model risk, and audit trails for LLM and agent-based systems.