Tovix is an AI agent testing and outcome evaluation platform. It evaluates production conversations for task success, factuality, safety, and interaction quality, surfaces repeated failure patterns, and turns real production failures into regression tests that run before every launch.

How is Tovix different from LLM observability tools like LangSmith or Langfuse?

Observability tools show you traces — what happened at each step. Tovix tells you whether the agent actually helped the user accomplish their goal. Traces don't tell you if the customer got help. Tovix evaluates outcomes, not just responses, and turns failures into regression test coverage automatically.

How does Tovix turn production failures into tests?

When Tovix detects a failure in a production conversation, it identifies the failure pattern and lets you recreate that scenario as an agent test with explicit success criteria. That test then runs before every future launch, so the same failure never reaches users again. The test suite grows automatically from real user failures.

What does Tovix cost?

Tovix costs $29 per 1,000 credits. Every new workspace gets 50 free credits on signup with no credit card required. One credit equals one conversation evaluation or agent test run. Credits expire after 90 days of inactivity.

Which AI agents does Tovix work with?

Tovix works with any conversational AI agent. It has native integrations for Salesforce Agentforce and Sierra, and supports any custom agent reachable via HTTP webhook. Conversations can be submitted via file upload or the public REST API.

Outcome First AI Agent Testing

Your users knew before you did.

Your AI agent has never crashed. It's failing users anyway. Tovix finds those failures and turns every one into a test. The same problem never ships twice.

Test Your Agent Now

No setup · 30 secs · No credit card · Works with any agent

↻ Production failures → regression tests, automatically

Outcome Failure Detected

Failure detected

User wanted to upgrade to the premium plan today. The agent explained features but did not guide the user through the upgrade path or help complete the purchase.

Signals

Misread the user intentDidn't complete the task

Annotated interaction

User:I want to upgrade to Premium today.

Agent:Premium includes advanced analytics, faster response times, and priority support.

User:That sounds good. Can you help me upgrade now?

Agent:Premium is a great choice for teams that need deeper insights and automation.

User:Yes, I want to switch. What do I need to do?

Agent:Many customers compare Premium with Enterprise before making a decision.

User:I do not need Enterprise. I just want to upgrade today.

Agent:Premium may also include onboarding support and special pricing depending on your account.

Root cause

Agent correctly identified purchase intent but never transitioned into the task flow needed to complete the upgrade. It stayed in feature explanation mode, failed to guide the next step, and introduced uncertain claims about pricing and entitlements instead of progressing the conversion.

Recommended fix

Define a clear upgrade handoff: after explicit buy intent, walk through checkout or escalate with next steps only. Add tests that fail when the agent keeps selling features after the user asks how to upgrade or complete purchase.

Example scores

Task16

Factuality82

Safety100

Experience26

Works withSalesforce Agentforce·Sierra·Custom agentsAll product names are trademarks of their respective owners.

200+

AI agents analyzed

The #1 failure is not hallucination. It is agents that answer the question asked, not the question meant.

Asked:“What business insurance options do you have for CA businesses?”
Agent:“Here are the minimum auto insurance requirements for California”Wrong answer

Asked:“What states do you serve? Any eligibility criteria to join?”
Agent:“What would you like to know about COVID-19?”Wrong answer

From our analysis of 200+ production AI agents across industries

AI agents fail in ways you don't see

Example failure

Agent:Premium is a great choice for teams that need deeper insights and automation.Didn't complete the task

They sound correct but are wrong
They break in edge cases
They miss user intent
They fail to be useful

Tovix finds these failures before your users do.

Every failure becomes a test. Automatically.

Observability tools show you what happened. Tovix turns what went wrong into proof it won't happen again — before the next launch.

↑ Containment rate↓ Human escalations↑ Regression-free releases

01

Monitor production

Every live conversation is ingested and evaluated automatically.

LIVE MONITORING

user “Switch me to the annual plan”

agent “Annual billing has great savings...”

CONTAINMENT

78%

ESCALATION

13%

04

Ship with confidence

Tests run before every launch so regressions never reach production.

PRE-LAUNCH CHECK

✓11 / 12 tests passed

✗1 regression blocked deploy

02

Find failures

Missed intent, unresolved tasks, and policy risk surface with evidence.

FAILURE DETECTED

TASK COMPLETION18/100

Identified intent but never guided user into the upgrade flow.

03

Build tests

Failures become reusable test scenarios for every future launch.

TEST CREATED

upgrade_intent
→ checkout_completion

Purchase intent suite · 12 scenarios

WHAT THIS LOOP DELIVERS

Containment rate

78%→91%

+13pp

Human escalations

21%→9%

−12pp

Days to catch regression

14d→2d

−86%

Illustrative outcomes - actual results vary by agent and deployment

What Tovix evaluates

✓Task success

✓Hallucination risk

✓Reasoning quality

✓Tone and user experience

✓User usefulness and engagement

✓Custom outcome metrics like containment, resolution, escalation, and policy compliance.

Testing & outcome evaluation

Failure patterns, ranked by impact

Tovix groups conversations with similar failure modes into named patterns. A pattern with 40 conversations averaging 38% task success is a known, repeating problem — not a one-off. Patterns are ranked by severity and count so your team fixes what hurts most before the next launch.

Custom evaluators for your business rules

Write a plain-English prompt and Tovix runs it as an LLM judge against every conversation. Flag responses that quote outdated prices, skip required disclosures, or break brand tone. Results are stored per interaction and exportable — so every compliance audit has an evidence trail.

Human review where it matters most

Tovix queues high-risk threads and unclear outcomes so people spend time on judgment, not every log line. Escalate the hard cases, keep a simple decision trail, and feed reviews back into trends automatically.

Eval library

Pre-built evaluations for every outcome

Start with production-ready pass-rate metrics and policy checks. Write your own in plain language when you need something custom.

Pass-Rate Metrics

METRIC

Containment Rate

Percent of interactions resolved within the AI channel without requiring a human agent.

METRIC

Customer Satisfaction Score

Proxy CSAT based on issue resolution, effort minimization, and tone.

METRIC

First Contact Resolution

Percent of issues fully resolved without a follow-up contact from the user.

METRIC

Response Completeness

Percent of interactions where all distinct user questions were fully answered.

METRIC

Self-Service Deflection Rate

Percent of interactions handled end-to-end by the AI without routing to a human.

METRIC

Proactive Help Rate

Percent of interactions where the agent anticipates and addresses likely follow-up questions.

Policy Checks

POLICY

Escalation Quality

When a handoff occurred, verifies it was warm, specific, and gave the user a clear path forward.

POLICY

Brand Voice Alignment

Checks that tone, terminology, and phrasing match the expected brand communication style.

POLICY

Compliance & Sensitive Guidance

Flags when the agent provides advice that crosses regulated or sensitive topic boundaries.

POLICY

Hallucination Risk

Flags responses containing specific facts or claims that appear fabricated or unverifiable.

POLICY

Instruction Following

Verifies the agent stays within its defined role, follows system guidelines, and resists jailbreaking.

POLICY

PII Exposure Risk

Flags interactions where personal information was exposed unnecessarily or in violation of policy.

+ Negative Sentiment Detection · Empathy & Acknowledgment · Multi-Turn Context Coherence · Task Success · and more

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Who it's for

Four roles. One shared problem: production AI that looks fine until your users feel it.

AI Product & Automation

You ship model updates without knowing if anything actually got better.

✓Turn production failures into regression test cases
✓Compare releases on real outcomes, not just eval scores
✓Catch regressions before users report them

Customer Success & Operations

Your containment rate looks fine. Your customers are still escalating.

✓Surface abandoned and unresolved threads you'd otherwise miss
✓Stack-rank repeated failure patterns by business impact
✓Know what to fix before it shows up in CSAT

Risk, Legal & AI Governance

Your agent said something you didn't approve. You found out from a complaint.

✓Route high-risk conversations to human review automatically
✓Document every decision with a full traceable audit trail
✓Verify that compliance fixes hold over time, not just on day one

Engineering & Platform

Your CI passes. Your agent still fails real users on Monday.

✓Wire regression tests from production failures into your CI pipeline
✓Run before every launch — catch regressions before users report them
✓Know which production scenarios your next build can actually handle

Pay per run. No subscriptions.

1 credit·Eval run·Test run·Agent analysis·Custom policy check

Free

50 credits, one-time starter allowance

-50 credits*
-Standard evals
-Human review
-30-day history

* Expires after 90 days of inactivity.

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Pro