Enterprises are moving into a new phase of automation.
Al agents are no longer experimental tools. They reason, make decisions, and act autonomously across platforms like:
Salesforce ServiceNow and other core enterprise systems.
So is the risk
The Trust Layer for the Agentic Enterprise
AI Quality Lifecycle Management
for Enterprise AI Agents
Provar TrustAI is built for this moment. It is the first enterprise platform designed to give technology leaders confidence that AI agents will behave predictably, securely, and in line with business and regulatory expectations — at scale.
Why TrustAI Exists
The AI Confidence Gap
AI innovation is moving faster than enterprise trust.
While agents are increasingly embedded in real workflows — handling customer interactions, operational decisions, and cross-system processes — most organizations lack the mechanisms to truly understand, validate, and govern how those agents behave.
Existing quality, testing, and governance models were designed for deterministic software. They were never built to assure systems that reason, adapt, and change over time.
AI initiatives stall in pilots
Risk accumulates quietly in production
Agents are not trusted with high value use cases.
Introducing Provar TrustAI
Provar TrustAI is the trust layer for the Agentic Enterprise.
It introduces a new discipline: AI Quality Lifecycle Management — a continuous approach to assuring AI agents from development through production.
TrustAI gives enterprises a single platform to:
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Validate agent behavior before deployment and continuously in production after release -
Detect drift, hallucinations, and unintended behavior early -
Produce clear, auditable evidence for governance, risk, and compliance -
Improve agent reliability and outcomes over time
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This is not a point-in-time control.It is continuous assurance for AI systems that never stand still.
- Discover
- Trust
- Optimize
A Practical Framework for Enterprise AI Assurance
TrustAI provides a clear view of your Agent estate. It shows what each agent does, what data it touches and how it interacts across systems, channels and processes.
Technology leaders gain a single, reliable source of truth for their Agent landscape - replacing fragmented views and assumptions with clarity.
Trust is earned through proof, not promises.
TrustAI continuously tests and validates agent behavior before and after deployment. It verifies that agents act accurately, securely, and within defined boundaries as data, models, and systems evolve.
Risky behavior, including hallucinations, drift, or policy violations, is identified early, with explainable evidence that supports audit, compliance, and executive accountability.
As AI expands, quality must improve, not degrade.
TrustAI connects real-world production behavior back into testing and validation, creating a closed loop that strengthens agent performance, reliability, and outcomes over time.
This allows organizations to scale AI with control, rather than accumulating risk.
Built for Real-World Agentic Systems
The platform is built on three core principles:
Why Provar
Defining the Category, Backed by Experience
Provar is uniquely positioned to lead this shift.
For more than a decade, Provar has helped some of the world’s largest enterprises assure quality across complex, highly regulated platforms.
TrustAI builds on that foundation, extending Provar’s expertise into AI-driven environments where traditional testing no longer applies.
Unlike legacy QA tools, observability platforms, or platform-specific guardrails, TrustAI:
Operates across platforms, not in isolated silos
Validates AI reasoning and outcomes, not just interfaces or APIs
Produces explainable, auditable evidence suitable for boards and regulators
Provides continuous assurance in production, not only pre-release checks
This is why Provar is first to market with a true AI Quality Lifecycle Management platform.
Availability
Provar TrustAI is available for select enterprise customers.
General Availability is Planned for April 2026
This is the foundation of trust for the Agentic Enterprise.