Custom agentic AI development for the production layer most prototypes never reach.

Three markers. (1) An eval harness that catches regressions on every commit, so you can prove the agent did not get worse last week. (2) An audit trail that lets you reconstruct any decision it made, so you can answer a regulator or settle a customer dispute. (3) Error handling that keeps a model-provider transient failure from cascading into a customer-facing incident. Observability and compliance integration compound those three. A demo can skip all five; a production agent cannot skip any.

8 to 12 engineer-weeks for a single agent capability shipped against a clean prototype on a vertical we have already shipped for. 16 to 24 weeks if the prototype needs significant rework, the regulatory surface is heavy, or it is the team's first production agent and Layers 4 and 5 are built from scratch. We tell you which bucket you are in by the end of Week 1, in writing, before we ask you to commit.

Yes, that is the most common shape. Bounded staff-augmentation: a small senior team that embeds in your repo, your CI, your model provider, and your incident-response rotation. We do not ask you to migrate to a Motomtech stack. We transfer the production-readiness pattern into your team during the engagement, so on hand-off your engineers operate the eval harness and observability dashboards, not us.

We have shipped under SOC 2 for financial-services clients. For HealthTech, we architect to HIPAA from day one: we execute a BAA with you and ensure BAAs are in place with every model provider in the agent's call path before the first production call. For SOC 2, we map the audit-trail and access-control layers to the relevant Common Criteria controls and provide documentation that drops into your auditor's evidence rubric.

Bounded staff-augmentation. Week 1 is scoping plus the eval harness; we agree on layer set, capability set, timeline, and team size before the build starts. No per-seat licensing, no committed headcount creep, no lock-in. Engagements typically run 8 to 24 weeks for a first production agent, and the build starts Week 2.

You do. Code, infrastructure, the eval harness, observability dashboards, and the audit-log pipeline are all yours at the end. We can stay on for a support and extension window, most clients keep us through the next major capability ship, but the IP and the operational pattern are yours from day one. No vendor lock-in built into the engagement.

We build with whatever you are using, we have shipped against Claude (Anthropic), GPT (OpenAI), and Gemini (Google) in production. The 5 layers are model-agnostic by design: they sit around the model call, not inside it. If you have a multi-provider strategy (a frontier-tier primary with a smaller-tier fallback), we wire the fallback into Layer 3 as a first-class pattern, not a workaround.

Two differences. First, we are a small senior team, not a marketplace and not a 1,000-engineer offshore shop. The engineers on your project have shipped production software for a decade and shipped production agents specifically; you meet them in Week 1. Second, we are an agentic-AI specialist. The audit-trail and multi-tenant patterns we shipped for Paramount Acceptance and Eptura are the exact engineering foundation the 5 layers require, and our cornerstone post walks through those layers with code.