Agentic AI development

The AI agent development companyfrom prototype to production

Custom AI agents built end to end: chat assistants, multi-agent orchestration, AI workflow automation, vector databases, and closed-loop evaluation - the same stack behind a live business we run ourselves.

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EvaluationLoop closed

System learning

How agents become systems

What we build

Agentic AI development services for complex builds

Agentic AI development is the discipline of building AI agents that plan, use tools, and act on real business workflows. We work on the architecture around the model: data foundations, agent coordination, the protocol layer agents call tools through, evaluation loops, and production workflows that keep improving after launch.

01System capability

Vector databases and data clustering

Retrieval, semantic search, and clustering turn messy business data into usable context - for AI agents, for analysts, for customer-facing products. It is the data foundation every custom AI agent depends on, and an agent without it is a very confident guess.

Vector database and clustering illustration

02System capability

Chat assistants, orchestration, and MCP servers

We build agentic chat experiences and multi-agent systems that plan, use tools, route work, and coordinate across APIs, documents, users, and internal software. MCP servers - Model Context Protocol servers - expose those same tools and data through one standard interface any MCP-compatible AI client can call, so a capability gets built once instead of once per assistant. We also support submission of MCP apps to Copilot, Claude, and OpenAI.

Agentic orchestration workflow illustration

03System capability

Closed-loop testing and self-learning systems

We build test harnesses where agents test agents, simulate realistic user behavior, and surface the failures a demo never shows. Those results feed back into self-learning systems that improve with each run, so enterprise AI agents stay reliable in production instead of staying exactly as good as the day they shipped.

Each capability has a page of its own: custom AI agent development, agentic chat assistants, multi-agent orchestration and AI workflow automation, vector databases and retrieval, closed-loop AI evaluation, MCP server development, and self-learning systems. The services overview explains how the seven fit together, and what agentic AI is covers the vocabulary first if the terms are new.

Proof, not promises

Products Fig AI Systems built and owns

Both products below are ours. Not client work, not prototypes: custom AI agent development, agentic chat assistants, and AI workflow automation running in real products - and one of them a live business we operate, with real orders and real money moving through it.

Live

Build-a-Dress

A live business we run: conversational dress design, automated quoting, and orders routed to verified makers.

2,000+monthly active usersMarketplace

School reportAnalyzing

ParseGradeReview

Demo

Report Grader

A demo for education teams: segmented parsing, agents mapped to a standards corpus, inspectors in the loop.

1,000+LLM call orchestrationEducation

Both are described in full under products: how the Build-a-Dress design assistant and quoting automation work, and how Report Grader grades school reports at high concurrency with a human in the loop. Build-a-Dress is a live business, at build-a-dress.com.

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Hiring AI agent developers, or scoping an agentic AI project? Send the workflow - the data behind it, the actions it has to take, and the standard a correct result is judged against.

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