AI Agent Development Company

A chatbot answers questions. An AI agent plans, reasons, and executes real actions — moving money, updating records, calling external systems — with grounded answers and a policy layer the model cannot override. We build the second kind: agentic systems where every action is validated, logged, and reversible if it needs to be.

Generative AI produces content. Agentic AI takes action. Agentic AI development means engineering the retrieval layer (knowledge graph + GraphRAG), the tool layer (MCP servers with scoped permissions), the evaluation layer (golden test set + critic gates), and the audit layer (immutable traces) — not just wrapping an LLM in a prompt. The generative pattern is one component of an agentic system, not the whole thing.

Custom. Every engagement is a scoped production pilot against your systems of record, your compliance regime, and your acceptance criteria — no shrink-wrapped agent platform, no shared model, no template. What is standard is the delivery pattern: 6 weeks, fixed price, grounded architecture, guarantee.

Structurally, not with prompt engineering. Agents retrieve from a knowledge graph over GraphRAG, so they can only cite entities that actually exist in your data; a critic agent checks every output against acceptance criteria before it ships; and a policy layer blocks any action the model tries to take outside its scope. Measured: 90% fewer unsupported answers versus baseline vector RAG in our internal test sets.

Primarily LangGraph for stateful agent orchestration; MCP servers for governed tool access; Neo4j for the knowledge graph; and model routing across Anthropic Claude, OpenAI, and open-weight LLMs (Llama, Mistral) depending on the compliance profile and where inference has to run. The evaluation and audit layers are framework-portable, so nothing is locked to one vendor.

Production pilots are fixed price and delivered in 6 weeks. Scope is agreed against your workflow, acceptance criteria, and reliability targets in writing before work starts. Multi-workflow programs scale from there. We scope precisely in the architecture briefing rather than publish a rate card — every engagement is different, and the guarantee (miss the criteria, the pilot is free) means we have to price it honestly.