Intelligent Enterprise AI

The compliant GenAI infrastructure that keeps enterprise agents production-ready — governed, secured and independently evaluated on our own stack.

ATX Agent Governance — The Governance Layer for Enterprise AI Agents

ATX Agent Governance brings evaluation, cost control, security, access control and monitoring for AI agents into one layer, so every agent you deploy is governed for risk, audit and compliance. It rests on three controls: access control (RBAC) keeps users and agents to the data they are authorised to see; budget control (FinOps) stops new requests once an agent hits its token budget; and the Control Center (AI Eval and observability) monitors every agent and alerts on any anomaly.

Inside, ATX AI Eval scores agents for quality, accuracy, safety and production readiness, using a three-judge LLM jury and agent-native metrics such as the CLEAR score and context drift. AI Security Eval red-teams agents before attackers can, Prompt Firewall blocks harmful and jailbreak prompts in real time, and Agent Observability brings eval scores, security activity and run traces into one dashboard. Install it with pip install atx-ai-govern.

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ATX KomplianceAI — Grounded Compliance Knowledge Plane

ATX KomplianceAI is a multi-tenant knowledge-base-as-a-service for regulatory compliance, callable by any AI agent over MCP. It ingests the regulatory corpus — statutes, agency rules, standards and guidance — alongside each customer's own policies, contracts and regulator correspondence, and serves citation-backed retrieval. It is a data plane, not a chatbot: every answer returns grounded, partial or no_answer, anchored to an immutable section version, effective date and source URL. Where the evidence falls short it refuses rather than guesses, so the agent in front of it escalates to a human instead of inventing a citation a regulator will later read.

Fourteen read tools ship over stdio and Streamable HTTP, with REST/OpenAPI and a typed Python SDK generated from the same registry — and every one of them passes a tenant-isolation chokepoint that re-checks the org scope of each row it returns. Bitemporal versioning answers what a rule said on any date without pinned citations drifting, a typed graph links each policy to the regulation behind it and flags the ones that no longer agree, and an append-only audit store carries a non-disableable seven-year retention floor. Administrative operations are never exposed over MCP or the SDK. It runs closed-network, in-VPC or fully air-gapped, so sensitive data never leaves your environment.

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ATX Voice AI — Private Voice AI for Regulated Industries

The ATX Sovereign Voice AI Stack is a private voice AI stack, hosted or local, that powers agentic AI applications in regulated industries such as BFSI, healthcare and government. Speech recognition, an agent layer and speech synthesis deploy as one unit on infrastructure you choose: it listens with streaming, multilingual speech to text, thinks by answering from your enterprise knowledge base — documents, policies, product data and systems — and speaks in a natural, human-like voice. Each turn waits through pauses until the caller is done, passes a safety check that protects sensitive details and a reply check for accuracy and compliance, and a caller can cut in at any time: the agent stops and listens.

Audio, transcripts and models stay inside your boundary, so there is no loss of data or IP, and data residency, audit trails and access control are built in for regulators. Replies start almost instantly, so live calls flow like a natural conversation, and conversation flows are configured to match your use case. It is POC-ready for Indic, EU and UK English use cases, and deploys on-premises in your data centre, in your own VPC and region, or ATX-hosted on dedicated single-tenant infrastructure — starting with a pilot on one use case.

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