AG
Agentic Giants
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“We do not publish a hallucination rate we cannot reproduce on a client’s dataset in the first week of the pilot.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