Solutions
Built for how
you actually work.
Not a generic chatbot. A verification platform that adapts its depth, its review process, and its output format to the stakes of your decision.
Code that reviews itself.
Kael generates code, then runs Track 2 against it. Security gaps, edge cases, logic errors, missing tests. You get the output of an internal review, not a first draft. Ship with confidence.
- ✓ Automated PR review with security scanning
- ✓ Self-checking code generation across 20+ languages
- ✓ Production debugging with root cause analysis
- ✓ Architecture decisions tagged with confidence levels
// Kael-generated API endpoint
export async function handlePayment(req) {
// Input validated, rate limited, idempotent
}
TRACK 2: Missing error handling for Stripe webhook signature verification. Adding try/catch with specific StripeSignatureError.
✓ 6 checks passed | 1 fix applied | Confidence: 0.94
Numbers you can actually cite.
Every projection, every comparison, every trend line gets tagged: verified against source data, or flagged for your review. No more second-guessing whether the AI made up a statistic.
- ✓ Quarterly report analysis with source verification
- ✓ Projection models tagged with assumptions and confidence
- ✓ Competitive analysis cross-referenced against filings
- ✓ Exportable audit trail for compliance review
Q3 Revenue Analysis
Revenue: $2.3M (+14.2% QoQ) [VERIFIED]
Operating margin: 18% [VERIFIED]
CAC: $47/customer [DATA NEEDED]
TRACK 2: Q2 included $180K one-time deal. Organic growth is 8.7%, not 14.2%. Recommend presenting both.
Research that cites its work.
Kael doesn't summarize and move on. It extracts claims, cross-references sources, and tells you which findings are verified vs. which need your judgment. Due diligence that holds up.
- ✓ Claim-level source verification across documents
- ✓ Contradiction detection across multiple sources
- ✓ Confidence scoring on every synthesized finding
research: market sizing - AI governance 2026
✓ 14 claims verified across 8 sources
● 3 claims conflict between sources - flagged
● 2 claims extrapolated - marked [NEEDS REVIEW]
Confidence: 0.87 | Sources: Gartner, IDC, internal data
Contracts reviewed clause by clause.
Upload a contract. Kael extracts every clause, identifies risk language, flags missing provisions, and tags each finding with a confidence level. Your associate's first pass, done in seconds.
- ✓ Clause-level risk identification and scoring
- ✓ Missing provision detection against standard templates
- ✓ Redline suggestions with confidence tags
Contract Review: SaaS Agreement v3.2
Section 4.1 - Liability Cap
⚠ Cap set at 1x annual fees. Industry standard is 2-3x.
Section 7.3 - Data Retention
✘ No deletion timeline specified. GDPR Art. 17 risk.
Section 9 - IP Assignment
✓ Standard work-for-hire language. No issues found.
Your team. Your rules.
Deploy domain-specific agents across your organization. Set custom verification policies. Define which outputs need human approval. Full audit trail on everything.
Unlimited Agents
Legal, finance, engineering, ops. Each calibrated to your standards.
Custom Rules
Define verification policies and confidence thresholds.
SSO / SAML
Enterprise identity management out of the box.
Audit Export
JSON or PDF. Full traceability for compliance.
7
Verification layers on every output
Find your workflow.
We're onboarding professionals and teams who need AI they can trust with real decisions. If you've been burned by outputs that sound right but aren't, this is built for you.
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