Wordaro
For engineering teams in regulated industries

Your AI is in production.
Can you prove every output was safe?

Wordaro lets engineering teams at fintech, healthcare, legal, and insurance companies validate AI outputs before they reach users — with deterministic rules, zero LLM calls, and a clear audit trail.

When your compliance team asks "how do we know the AI didn't say something wrong?" — this is your answer.

Start free — no card requiredSee use cases
Built forFintech & BankingHealthcare & MedTechLegal TechInsuranceHR & Recruiting AIGov Tech

Use cases

Who uses Wordaro

Engineering teams whose AI outputs have real-world consequences — and who need to prove it.

🏦Fintech

AI loan decisions & financial advice

Your AI assistant explains loan denials or investment options. One hedge phrase or missing required disclosure and you're facing regulatory review.

Rules you'd set
  • No hedge language in decisions
  • Required disclosure fields
  • Forbidden phrases (guarantees, certainty)
🏥Healthcare

Clinical summaries & patient-facing AI

Your AI summarises patient notes or answers health questions. A missing field or leaked PII isn't a bug — it's a HIPAA violation.

Rules you'd set
  • Required fields (diagnosis, date)
  • No PII in outputs
  • No speculative language
⚖️Legal Tech

Contract analysis & document generation

Your AI drafts contract clauses or analyses legal risk. Vague language or missing required terms creates liability for your customers.

Rules you'd set
  • Required clause presence
  • Forbidden speculative language
  • JSON schema for structured output
🛡️Insurance

Claims processing & coverage explanations

Your AI explains coverage decisions to policyholders. An uncertain or incomplete response triggers complaints and regulator attention.

Rules you'd set
  • No hedge language
  • Required fields (policy number, reason)
  • Allowed values for decision type
👥HR & Recruiting AI

Job descriptions & candidate screening

Your AI writes job descriptions or scores candidates. Discriminatory language or missing equal opportunity statements create legal exposure.

Rules you'd set
  • Forbidden patterns (age, gender bias)
  • Required EEO statements
  • Max length compliance
🏛️Government Tech

Citizen-facing AI responses

Your AI answers questions about benefits, permits, or services. A wrong answer or uncertain phrasing undermines public trust and creates accountability risk.

Rules you'd set
  • No hedge language
  • Required citation fields
  • Forbidden speculation patterns

The obvious question

"Why not just prompt GPT-4 to check our outputs?"

You can. But when your compliance team or a regulator asks to see the audit trail, "we asked another AI to check it" is not a defensible answer.

✓
Deterministic
Same input, same result, every time. Required for reproducible compliance evidence.
✓
No hallucination risk in the validator
An LLM validator can itself make mistakes. Wordaro's rules are pure code — they cannot hallucinate.
✓
< 10ms, not 2–3 seconds
Fast enough to gate outputs inline before they reach users. LLM validation breaks real-time pipelines.

API

One API call. Instant verdict.

Drop it anywhere in your AI pipeline — before the output reaches the user.

POST /api/enterprise/validate — fintech loan decision
AI output submitted
{
  "decision": "denied",
  "reason": "I think your
  credit score might be
  too low at this time.",
  "disclosure": null
}
Validation result BLOCKED
{
  "result": "fail",
  "violations": [
    {
      "type": "no_hedge_language",
      "message": "Hedge: 'I think'"
    },
    {
      "type": "required_field",
      "message": "disclosure is null"
    }
  ],
  "llm_calls": 0,
  "latency_ms": 6
}

Output blocked before reaching the user. Retry triggered. Zero model fees spent on validation.

Process

How it works

Three steps. Fits into any existing AI pipeline in under an hour.

01

Define your rules

Use the dashboard to build rule sets for your specific AI use case — required fields, forbidden phrases, PII checks, JSON schema, hedge language. No code required to configure.

02

Validate before it ships

Call POST /api/enterprise/validate from your pipeline. If the output fails, block or retry before the user ever sees it. Results in under 10ms — fast enough for real-time use.

03

Show your compliance team

Every rule is explicit and readable. When someone asks how you know the AI didn't say something wrong, you can show them exactly which rules ran and why each output passed or failed.

Rules

10 built-in rule types

Pure code. No ML. Every rule behaves exactly the same way every time.

required_field
Field must exist & be non-empty
forbidden_pattern
Block specific strings or phrases
max_length
Hard cap on output length
min_length
Minimum content requirement
regex_match
Must / must not match pattern
allowed_values
Enumerated value enforcement
no_pii
Email, phone, SSN, IP detection
json_schema
Full JSON Schema validation
no_hedge_language
25+ uncertainty markers blocked
key_value_present
Multi-field presence check
< 10ms
Median validation latency
0
LLM calls to validate
100%
Deterministic — same input, same result
10
Built-in rule types

Pricing

Simple, usage-based pricing

Pay for validations. No per-seat fees. No model costs.

Free
$0

Test your rule sets in the playground before committing.

  • 100 validations / mo
  • 1 rule set
  • Playground only (no API)
Try the playground
Starter
$19/month

For individual developers integrating validation into production AI features.

  • 10,000 validations / mo
  • 10 rule sets
  • 3 workspaces
  • REST API access
  • Batch validate (25 / call)
Start Starter plan
Most popular
Pro
$49/month

For teams shipping multiple AI features with compliance requirements.

  • 50,000 validations / mo
  • Unlimited rule sets
  • 5 workspaces
  • REST API access
  • Batch validate (100 / call)
  • Priority support
Start Pro plan

Your compliance team is already asking. Now you have an answer.

Add AI output validation to your pipeline in one API call. Free to start.

Start free — no card required