Agentic Data Architecture (Ada): Eliminating The Api Layer For Hallucination-Free, Sub-100ms Enterprise AI Agents

Nirmal Nambiar

doi:10.63363/aijfr.2026.v07i02.4079

Agentic Data Architecture (Ada): Eliminating The Api Layer For Hallucination-Free, Sub-100ms Enterprise AI Agents

Author(s)	Mr. Nirmal Nambiar
Country	India
Abstract	Every major framework for deploying AI agents in production shares one unexamined assumption: data must be accessed through a network boundary. Whether via the Model Context Protocol (MCP), CLI wrappers, or direct REST APIs, the agent must leave its execution context, traverse a network, authenticate, and re-enter reasoning for every data lookup. This boundary is the structural root cause of the three most damaging enterprise AI failure modes: hallucination (15-25% error rate, $250M annual industry loss), prohibitive latency (200-500ms per API round-trip), and single-agent throughput ceilings that prevent elastic scaling. We present Agentic Data Architecture (ADA), a framework that eliminates this assumption through three mutually reinforcing mechanisms: (i) direct polyglot database connectivity, native async connections to PostgreSQL, MongoDB, and Redis bypassing all HTTP intermediaries; (ii) per-subtask RAG grounding, Sentence-BERT embeddings and HNSW vector retrieval invoked inside each specialist agent's reasoning loop rather than as a global preprocessing step; and (iii) hierarchical multi-agent orchestration, a Controller Agent that decomposes queries into a DAG of subtasks, dispatched to stateless Specialist Agents via a work-stealing scheduler. Evaluation across 10,000 enterprise queries spanning customer support, financial analytics, HR intelligence, product knowledge, and operational data demonstrates: 70% hallucination reduction (22.4% to 4.2%), 81.4% latency reduction (350ms to 65ms), 6.7x throughput gain at ten parallel agents, and 92.5% retrieval accuracy. All results are achieved on consumer-grade hardware (Intel i7, 16GB RAM), with no GPU and no cloud API dependency, establishing ADA as a production-viable architecture for cost-constrained enterprise deployments.
Keywords	Agentic AI, Direct Database Access, Hallucination Mitigation, Multi-Agent Orchestration, Retrieval-Augmented Generation, Low-Latency Inference, Enterprise Ai, Work-Stealing Scheduler, Beehive Architecture
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 2, March-April 2026
Published On	2026-03-18
DOI	https://doi.org/10.63363/aijfr.2026.v07i02.4079

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Agentic Data Architecture (Ada): Eliminating The Api Layer For Hallucination-Free, Sub-100ms Enterprise AI Agents

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