--- title: TrustAI - Provar image: https://go.provar.com/hubfs/featured-image.png --- ![TrustAI](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/trustai-main-nav-logo.png?width=215&height=26&name=trustai-main-nav-logo.png) [Platform](https://go.provar.com/trustai#platform) [Application Testing](https://go.provar.com/trustai#functional) [Agent Evaluation](https://go.provar.com/trustai#agent-eval) [By Role](https://go.provar.com/trustai#by-role) [Talk To Us](https://cta-eu1.hubspot.com/web-interactives/public/v1/track/click?encryptedPayload=AVxigLKLgj0w%2FKgbLv5%2B6ei69Og%2BN%2BduDkc58tJxByJWZGtNlh91w5phQLavKz2QBNKyRk96pkwbeXdTKqEPxv8O27rAsNFPtnmxhF1whaVRZS4BHelRXWs7reAf8U74WaFcjSGsBPot2WpbFJJcc4aUKEgoH684KBrh3no3B7e0o6YJq7vCMsVlVyg2MDJBi%2Fb9LurB2mu0csCjHg%3D%3D&portalId=139735407) # Can you trust the quality of your increasingly autonomous enterprise? AI now builds your software and runs your business processes. Both move faster than any team can verify by hand. TrustAI gives you continuous evidence that your applications and your AI agents behave as expected. [Talk To Us](https://cta-eu1.hubspot.com/web-interactives/public/v1/track/click?encryptedPayload=AVxigLKLgj0w%2FKgbLv5%2B6ei69Og%2BN%2BduDkc58tJxByJWZGtNlh91w5phQLavKz2QBNKyRk96pkwbeXdTKqEPxv8O27rAsNFPtnmxhF1whaVRZS4BHelRXWs7reAf8U74WaFcjSGsBPot2WpbFJJcc4aUKEgoH684KBrh3no3B7e0o6YJq7vCMsVlVyg2MDJBi%2Fb9LurB2mu0csCjHg%3D%3D&portalId=139735407) [See How it Works](https://cta-eu1.hubspot.com/web-interactives/public/v1/track/click?encryptedPayload=AVxigLKECL1RuRFsPQGRE6WZhMp4alvJeB5ULTtut0Ofo1YZ9VZudzSQXJclgB6b%2Brut6yqpSikGOwGLUPIOU1ln2nT4hVb0fukKrUlr0EOuZmfBW6qXlCzLJdPO%2FuFvYhosPyLS8vay7Nxr8ejBWqYfCy5iE42LFkj%2FQW4Cx%2BkITT4q75PXbafOu1q98QXwkTW50kyNjioYMx%2Bp&portalId=139735407) ![Applications, agents, and documents connected to a shield](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/hero-diagram.png?width=884&height=792&name=hero-diagram.png) WHAT YOU BUILD ## Applications Validate what your team — and its AI tools — build. WHAT YOU RUN ## AI agents Evaluate what your agents actually do. TOGETHER ## One evidence trail One platform across applications and agents. ## Every enterprise now has two quality problems. Enterprise software is becoming autonomous on two fronts at once: in what gets built, because AI increasingly writes it, and in what runs on its own, because agents increasingly act without a human in the loop. ![Applications](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-applications.png?width=78&height=78&name=icon-applications.png) WHAT YOU BUILD ### Applications - INCREASINGLY AI-authored software - DISCIPLINE Functional quality - VALIDATED BY TrustAI Functional ![AI Agents](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-agents.png?width=78&height=78&name=icon-agents.png) WHAT YOU RUN ### AI Agents - INCREASINGLY Autonomous agent behavior - DISCIPLINE Agent evaluation - VALIDATED BY TrustAI Agent Eval One platform. One evidence trail. ## AI changes what software looks like. It also changes how software must be tested. Yesterday People built software. We tested software. Today AI builds software. AI runs software. We need to validate both. ![Shield](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-shield.png?width=107&height=107&name=icon-shield.png) ## What we mean by trust. Evidence that software and agents behave as expected, under the conditions that matter, and can be validated continuously as they change. TrustAI is not - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) AI Safety - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) AI governance - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) Agent observability alone - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) AI Security Those are real, adjacent concerns. TrustAI does something more specific: it produces evidence that what you built and what you run behave the way you expect, and it keeps producing that evidence as they change. ## One platform, two engines. AI now produces more than any team can verify by hand, in what they ship and in what they run. TrustAI validates both from one place. ![TrustAI Functional icon](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-functional.png?width=78&height=78&name=icon-functional.png) VALIDATES WHAT YOU BUILD ### TrustAI Functional Validates the software your team, and its AI tools, build. An intent-based agentic testing engine across Salesforce, web and mobile. - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-check.svg) State the business requirement once, in plain language - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-check.svg) Grounded in your org's metadata: objects, fields and components, not HTML - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-check.svg) Every run produces traceable, release-ready evidence ![TrustAI Agent Eval icon](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-agent-eval.png?width=78&height=78&name=icon-agent-eval.png) VALIDATES WHAT YOU RUN ### TrustAI Agent Eval Validates what your agents do. Stress-tested across personas, graded by calibrated evaluators. - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-check.svg) Simulate real, multi-turn conversations - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-check.svg) Evaluate responses against the criteria and business rules you define - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-check.svg) Re-evaluate every time a prompt, model or agent changes Better together ## The only platform that validates everything AI touches. One worldview, one category, one buyer conversation and one budget line. On their own, point tools are easy to defer and easy to swap. Together they give you one continuous source of evidence. ## Most tools make test creation faster. We're changing what a test is. AI has changed how much software gets built, not how much of it gets safely checked. Your teams, and their AI coding tools, now ship Salesforce, web and mobile changes faster than anyone can verify by hand. The validation bottleneck is the new delivery bottleneck. ![Applications, agents, and documents connected to a shield](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/stats-intro-diagram.png?width=520&height=400&name=stats-intro-diagram.png) ![Weeks icon](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/stat-icon-weeks.png?width=53&height=53&name=stat-icon-weeks.png) 4-8 WEEKS Of senior engineer time to hand-build a production-ready Playwright framework for Salesforce Need "We need to release Salesforce changes faster, and do it with proof that every critical requirement still works, all without scaling QA headcount." ![Year icon](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/stat-icon-year.png?width=53&height=53&name=stat-icon-year.png) 3x A YEAR Salesforce seasonal releases break DOM-based locators, and the locator hunt starts again Urgency "AI is increasing the volume and pace of change. If validation stays manual, functional testing becomes the bottleneck on every release." ![Tokens icon](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/stat-icon-tokens.png?width=53&height=53&name=stat-icon-tokens.png) ~114K TOKENS Streamed as DOM into an AI agent's context in a single Playwright MCP test session Blocker "Legacy automation consumes the team with maintenance. Generic AI can generate scripts, but not Salesforce-native, repeatable validation with traceable evidence." What Salesforce QA leaders are telling us ## The durable asset is the intent. You state the guarantee: the business requirement, in plain language. TrustAI works out how to prove it against your product as it exists right now, and keeps the evidence. Not the locator, the script or the recording. Script-based tools and AI coding agents see an anonymous accessibility tree. TrustAI grounds the AI in your org's actual metadata, so it holds steady across environments and seasonal releases. Breaks Script step page.getByRole('textbox', { name: 'Discount %' }) .fill('15'); Generic element reference. After a release renames the field, a locator-healer can guess a new selector, but the requirement is lost. Holds Intent Requirement: A sales rep can apply up to 15% discount on an Opportunity without approval. Grounded in: Opportunity · Discount\_Percent\_\_c · Lightning record page TrustAI resolves the current path at run time and traces the result back to the requirement. Illustrative example --- ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-paint.svg) ### The intent survives the UI. Describe the business outcome once. TrustAI resolves the current path at run time, so DOM churn stops being a permanent maintenance job. ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-user.svg) ### Agentic where it matters, human where it counts. TrustAI plans, runs, recovers, debugs and reports, while approvals and review stay visible. No silent healing, no mystery green checks. ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-skyline.svg) ### Built for the enterprise, not a demo app. Salesforce is first-class, with web and mobile built into the direction. Every run produces the evidence you need to validate, debug, report and release. --- Turn every requirement into release-ready proof ### Coverage grows. Maintenance debt doesn't. The engine absorbs more of the brittle work as your coverage expands. ### QA stops being the gate everyone waits on. Validation becomes a continuous capability, not a release-week scramble. ### Release decisions stop being opinions. Every answer traces to the requirement it validates, the evidence behind it and the risk it closes. ## Testing execution isn't the same as evaluating intelligence. A traditional test has a deterministic outcome: same input, same result, pass or fail. An agent can reach an outcome by different paths, word it a dozen ways, and still satisfy an assertion that only checks that something came back. ![Evaluating intelligence diagram](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/eval-intelligence-diagram.png?width=636&height=364&name=eval-intelligence-diagram.png) AUTOMATION ### Tells you what happened. EVALUATION ### Tells you whether it was right. TRUST ### Comes from having evidence. --- ## An agent can pass your test and still get it wrong. It can run cleanly through your test flow and still: - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) Give an incomplete answer - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) Take the wrong action - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) Violate a business rule - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) Reach the right outcome for the wrong reason - ![](https://go.provar.com/hubfs/Microsite/TrustAI/icon-pill-close.svg) Behave differently depending on the prompt or context None of these throw an error, and most won't fail a conventional assertion. Evaluation starts with defining what "good" means (the criteria, the business rules, how much variation is acceptable) and then applying those criteria the same way every time. service-agent · run 0412 ILLUSTRATIVE EXAMPLE CUSTOMER I was charged twice for my March order. Can you refund the duplicate? AGENT I'm sorry about that. I've issued a full refund for your March order. You'll see it in 3–5 business days. SCRIPTED ASSERTION PASS response.status == 200 response.text != "" flow completed AGENT EVALUATION FAIL Refunded the full order, not the duplicate charge Rule: refunds above limit need approval ## Agent testing as an engineering discipline. TrustAI brings the rigor you already apply to automation to agent behavior. The workflow will feel familiar. 1. 1 ### Define Set the criteria, business rules and acceptable variation for "good". 2. 2 ### Simulate Run realistic, multi-turn conversations across personas and edge cases. 3. 3 ### Evaluate Grade every response against your criteria with calibrated evaluators. 4. 4 ### Identify failures See where agents answer incompletely, act wrongly or break policy. 5. 5 ### Iterate Fix prompts, data or configuration with the evidence in hand. 6. 6 ### Re-evaluate Re-run automatically as prompts, models and agents change. What TrustAI Agent Eval covers ### AI-agent specific test automation Tests built for how agents behave, not for deterministic scripts. ### Agent reliability and quality scoring Calibrated evaluators score every response against your criteria. ### Autonomous regression testing for agents Re-runs automatically when prompts, models or agents change. ### Simulation environments (“digital sandboxes”) Rehearse agents against personas and edge cases before production. ### Agent observability and tracing See the path an agent took, not just where it ended up. ### Compliance evidence generation Every run leaves a record you can point to when it matters. ### Security and redteam testing for agents Probe agents with adversarial inputs before someone else does. ### Multi-agent workflow validation Validate the hand-offs when agents work together. Works across platform ecosystems - Microsoft - Salesforce - ServiceNow - AWS - Google ## The real alternative isn't a competitor. It's doing it by hand. Trust breaks down the same way on both fronts: to manual effort and brittle scripts that can't keep pace. The market is moving through three stages of maturity. STAGE 1 ### Manual QA Can't scale with autonomous systems. STAGE 2 ### Generic AI + scripts Can generate tests, but doesn't understand the application or validate it continuously. STAGE 3 ### Provar + TrustAI Purpose-built, continuous validation for enterprise applications and autonomous agents. ![Warning](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-warning.png?width=78&height=78&name=icon-warning.png) FUNCTIONAL ### vs. Playwright and generic AI coding agents - ✕ Work from an anonymous accessibility tree: no field API names, no component types - ✕ 4–8 weeks of senior engineer time to hand-build a production-ready Salesforce framework - ✕ Seasonal releases, three a year, break DOM-based locators - ✕ A locator-healing agent can fix a selector. It can't recover from a renamed field. --- TrustAI grounds the AI in Salesforce objects, fields, component types and page objects, which stay stable across environments and releases. THE DIFFERENCE ![Warning](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/icon-warning.png?width=78&height=78&name=icon-warning.png) AGENT EVAL ### vs. manual QA - ✕ No comparable automated alternative exists today - ✕ Manual review can't keep pace with multi-turn, nondeterministic agents - ✕ Every prompt or model change reopens all prior testing --- "We're blocked from releasing until we validate agents work, with evidence we can trust." FROM AN AGENT EVALUATION DISCOVERY CALL --- ## Same gap, seen from where you sit. AI and Innovation Leaders QA and Test Automation Developers and Automation Engineers AI and Innovation Leaders ### The AI confidence gap is now a testing problem. --- THE QUESTION YOU'RE ASKING "My AI works. But can I prove it's ready to scale?" A successful demo, a successful pilot and a reliable enterprise deployment are three different things. In a demo, someone controls the conversation. In production, no one does. Agent evaluation is part of the infrastructure you need to scale enterprise AI safely. WHAT PRODUCTION WILL BRING - ✕ Unexpected questions and ambiguous requests - ✕ Edge cases and changing data - ✕ Different personas - ✕ Policy constraints YOUR PATH WITH TRUSTAI Test ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Evaluate ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Measure ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Improve ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Deploy QA and Test Automation ### Your tests passed. Did the agent get it right? --- THE QUESTION YOU'RE ASKING "My automation passes. But did the agent actually do the right thing?" You already know how to automate. Agents change what "correct" means. Coverage tells you the interaction executed, not whether the agent made the right decision. That's a new layer of testing, and it needs to be repeatable at scale. WHAT TRUSTAI GIVES YOUR TEAM - ✓ Simulate real conversations - ✓ Evaluate responses against defined criteria - ✓ Test at scale - ✓ Identify failures - ✓ Re-evaluate continuously as agents change YOUR PATH WITH TRUSTAI Simulate ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Evaluate ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Scale ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Identify ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Re-evaluate Developers and Automation Engineers ### AI can generate tests. Who evaluates the results? --- THE QUESTION YOU'RE ASKING "My AI coding agent generated the test. But who validates the result?" Whether you build with Playwright, an AI coding assistant or your existing framework, generating a script is getting faster. Knowing the script proves something is where the risk is moving. Pass/fail assertions were built for deterministic systems. Agents need criteria that can tell a good answer from a plausible one. WHAT GETS HARDER WITH AN AGENT IN THE LOOP - ✕ Non-deterministic responses - ✕ Evaluating natural-language output - ✕ Expected vs. acceptable outcomes - ✕ Regression as agents change - ✕ Agent and MCP interactions YOUR PATH WITH TRUSTAI Define ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Simulate ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Evaluate ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Identify ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Iterate ![](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/gap-path-arrow.png?width=64&height=64&name=gap-path-arrow.png) Re-evaluate ![Provar TrustAI](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/trustai-cta-logo.png?width=219&height=26&name=trustai-cta-logo.png) ## Build evidence before you scale. AI adoption shouldn't depend on trust alone. It should be backed by evidence. Move from "we believe it works" to "we can show it works." [Talk To Us](https://cta-eu1.hubspot.com/web-interactives/public/v1/track/click?encryptedPayload=AVxigLKLgj0w%2FKgbLv5%2B6ei69Og%2BN%2BduDkc58tJxByJWZGtNlh91w5phQLavKz2QBNKyRk96pkwbeXdTKqEPxv8O27rAsNFPtnmxhF1whaVRZS4BHelRXWs7reAf8U74WaFcjSGsBPot2WpbFJJcc4aUKEgoH684KBrh3no3B7e0o6YJq7vCMsVlVyg2MDJBi%2Fb9LurB2mu0csCjHg%3D%3D&portalId=139735407) ![TrustAI](https://go.provar.com/hs-fs/hubfs/Microsite/TrustAI/trustai-main-nav-logo.png?width=215&height=26&name=trustai-main-nav-logo.png) THE ENTERPRISE QUALITY PLATFORM FOR THE INCREASINGLY AUTONOMOUS ENTERPRISE