AI Architect · Agentic Giants

Ahsan Ishfaq

Ahsan Ishfaq is the AI Architect at Agentic Giants, an AI agent development company in Aubrey, Texas. He owns the target-state architecture and buy-vs-build decision on every advisory engagement, and authored the measurement protocol behind the 90% unsupported-answer reduction figure documented on /proof. 12+ years of production engineering experience across payment platforms, enterprise knowledge graphs, and agentic systems.

What Ahsan Owns on Every Engagement

  • Target-state architecture. Every advisory engagement (see Agentic AI Consulting) is scoped, signed, and delivered under Ahsan’s name — never a rotating pool.
  • The measurement protocol behind /proof. The 90% unsupported-answer reduction figure and the 500-query evaluation set methodology were authored by Ahsan and reviewed by Ahmad Ishfaq before publication.
  • The Guaranteed Pilot standard. Every pilot ships against a written acceptance criterion Ahsan signs before the engagement begins. See /proof#guaranteed-pilot for the standard.

“We do not publish a hallucination rate we cannot reproduce on a client’s dataset in the first week of the pilot. The 90% figure is a floor, not a ceiling — it is the number we are comfortable defending against a matched baseline in every engagement we have shipped.”

Published on /proof, updated 2026-09-14.

Areas of Expertise

Enterprise knowledge graphs and GraphRAG architecture

Ahsan Ishfaq designs enterprise knowledge graph and GraphRAG architectures for regulated buyers — the retrieval layer that produces the 90% reduction in unsupported answers versus baseline vector RAG documented on /proof. Neo4j, RDF, and property-graph modelling; hybrid vector-plus-graph retrieval; per-fact provenance and citation.

Every architecture ships with an evaluation harness so the buyer's team can score outputs after Agentic Giants exits. See /services/graphrag-implementation for the delivery pattern.

MCP server design and least-privilege tool scoping

Ahsan Ishfaq designs Model Context Protocol servers that give AI agents governed access to enterprise systems — least-privilege tool scoping, prompt-injection defenses, human-in-the-loop approval on state-changing calls, and immutable per-action audit logs. The MCP layer is the piece of the stack a Security Officer reviews first.

See /services/mcp-security for the delivery pattern; see /proof#soc-2-delivery for the SOC 2 Type II posture the MCP layer is built against.

Fixed-scope advisory engagements for regulated buyers

Ahsan Ishfaq leads the advisory engagements where the target architecture, buy-vs-build decision, evaluation harness design, and written pilot acceptance criteria for an enterprise agentic AI program are produced in two to four weeks. Every artifact is portable — if the implementation phase goes to another vendor, the client keeps the documents.

This is the delivery pattern on /services/agentic-ai-consulting. Ahsan is the named architect on the engagement contract.

Where Ahsan’s work appears on the site