Product

Four phases. One accountability platform.

From open-source SDK to enterprise governance platform in 24 months. Each phase delivers a complete, deployable product — built on the same canonical data model.

Capture · Comply · Enforce · Govern

The four-phase architecture

Each phase ships a complete product for a specific buyer — and extends the same accountability graph the previous phase built.

Phase 01
01

Capture

Months 0–3
Primary user
ML Engineer / Agent Developer

Drop-in instrumentation for production agent pipelines. The open-source SDK that turns any LangGraph, CrewAI, or AutoGen workflow into a tamper-evident Decision and Action stream.

Core deliverables
  • @providex.trace decorator: LangGraph, CrewAI, AutoGen
  • Action records: SHA-256 hash-chained, tamper-evident
  • Approval records: every HiTL checkpoint outcome logged
  • CLI verify: VALID / TAMPERED in under 30 seconds
Exit metric< 10 minutes to first record
Phase 02
02

Comply

Months 3–9
Primary user
Compliance Officer / DPO

The compliance intelligence layer. Agent inventory, regulatory framework mapping, and one-click audit reports — without filing an engineering ticket.

Core deliverables
  • Agent inventory dashboard: every deployed agent registered
  • Session + Decision + Action timeline: the full why + what
  • Framework mapping: SOC 2, HIPAA, EU AI Act Article 12/13/14
  • One-click audit report: PDF/Word, hash-chain proof included
  • Langfuse / Galileo connector: traces become audit evidence
Exit metricCompliance report in under 5 minutes, no engineering
Phase 03
03

Enforce

Months 9–18
Primary user
CISO / Head of AI Security

Runtime policy enforcement and incident response. Cedar/OPA policies evaluated against every Action, statistical anomaly detection, and bi-directional integrations with the AI security platforms you already run.

Core deliverables
  • Policy-as-code engine: Cedar/OPA evaluates every Action
  • Anomaly detection: statistical baseline, auto-creates Incidents
  • Zenity / Rubrik integration: agent discovery enriches Agent entity
  • SIEM/SOAR streaming: Incidents flow to Datadog, Splunk, PagerDuty
Exit metricIncident alert delivered < 60 seconds after detection
Phase 04
04

Govern

Months 18–24
Primary user
Head of AI Governance / Board

The cross-platform governance fabric. Multi-system correlation, policy simulation before live deployment, and GRC connectors that make Providex the platform of record for enterprise AI accountability.

Core deliverables
  • Cross-system correlation: multi-agent, multi-platform workflows
  • Policy simulation: what-if analysis before live deployment
  • GRC connectors: Credo AI, Holistic AI, ServiceNow
  • Board analytics: override trends, incident rates, posture scores
Exit metricPlatform of record for enterprise AI accountability
Phase 1 — Capture

Open-source SDK. One decorator. Full provenance.

The Capture SDK wraps your existing agent tool calls and emits a Decision + Action record for each invocation. Hash-chained, tamper-evident, and indistinguishable from your current pipeline from the outside.

Drop-in decorator

@providex.trace wraps any Python function. Works with LangGraph, CrewAI, AutoGen, or custom agents.

< 5ms overhead

Async, batched writes. Your agents won't notice the difference.

Tamper-evident by design

Every Action is SHA-256 hash-chained to its predecessor. A single modification breaks the chain.

HiTL Approval records

Built-in authorization checkpoints. Every approval logged with full Decision context.

tools.pypython
from providex import trace, authorize
from langchain.tools import tool

@trace(action="query_database", require_auth=True)
@tool
def query_database(query: str) -> dict:
    """Query the customer database."""
    auth = await authorize(
        action="query_database",
        context={"query": query, "risk": "high"}
    )
    if not auth.approved:
        return {"error": "Authorization denied"}

    result = db.execute(query)
    return {"rows": result.rows, "count": len(result)}

Seven entities. One accountability graph.

The Providex data model captures not just what agents did, but why they decided to do it — and under whose authority.

Agent

Who deployed the AI, what it's permitted to do.

Session

One workflow run — objective, time window, outcome.

The missing layer

Decision

Why the agent chose this action — the missing layer.

Action

What the agent did — tamper-evident, hash-chained.

Policy

The rule that governs this action, with regulatory refs.

Approval

Who authorized it, with what context, when.

Incident

The investigation record when something goes wrong.

Decision is the entity no other platform captures. It's the difference between a log and an alibi.

Packaging & Pricing

Three editions designed to meet you where you are — from early experimentation to full enterprise governance.

Developer / Team Edition

Land

For platform teams and advanced developers piloting agentic workflows.

  • Core SDKs
  • Agent inventory
  • Session and decision timelines
  • Basic policy-as-code checks
  • Lightweight approval flows

Faster debugging and safer experimentation before enterprise-wide rollout.

Get Started
Recommended

Enterprise Standard

Expand

For AI governance and risk teams in regulated enterprises.

  • All Developer Edition features
  • EU AI Act-aligned logging profiles and report templates
  • Integrations with GRC, AI governance tools, and major SIEMs
  • Role-based access controls
  • Data residency options
  • Advanced retention policies

Enterprise-grade governance with compliance frameworks built in.

Get Early Access

Enterprise Custom

Security & Compliance Add-On

For CISOs and security operations teams with advanced requirements.

  • All Enterprise Standard features
  • Deeper integrations with AI security platforms
  • Enhanced incident workflows
  • Correlation with security events
  • Custom compliance framework packs (EU AI Act, banking, healthcare)
  • Advanced analytics modules

Full-spectrum security and compliance tailored to your organization.

Contact Us

Hybrid Pricing Model

  • •Base platform fee per tenant reflecting compliance value and feature tier
  • •Usage-based metering tied to volume of decisions or actions recorded (not prompts alone), aligned with observability pricing practices
  • •Add-on bundles for high-value connectors (e.g., EU AI Act pack, banking/healthcare regulatory packs) and advanced analytics modules