Zero-Trust AI Incident Response
for FinTech.
The autonomous incident agent that scrubs secrets and PII inside your VPC — using three independent detection layers — before model inference. Regex, entropy analysis, and local ML each independently verify the payload. Keep engineering velocity while preserving audit posture.
SOC 2 Type II-ready architecture · PCI-DSS-aligned controls · DORA-oriented operations
Android available now. iOS coming soon.
Resolve faster
AI investigates the moment alerts fire. Root cause in seconds, not minutes.
Less alert fatigue
Context and suggested fixes before you're fully awake. Page only when it matters.
Keep building
Handles the first 90% of incident response so your team can focus on shipping.
From alert to resolution in four steps.
No runbooks. No context-switching. No waking up the whole team.
Alert fires
PagerDuty, Datadog, CloudWatch, or any webhook POSTs to your CollAI endpoint.
Three-layer sanitization
Regex strips known patterns. Entropy analysis catches obfuscated secrets. A local ML model identifies contextual PII that neither layer can see.
Proposed fix
The AI proposes a specific action — restart instance, revert commit, scale pods — with a clear risk assessment.
You approve (or don't)
Tap approve on your phone or type it in chat. Nothing runs without your explicit approval.
You control the boundary.
Most “AI incident tools” ask you to paste logs into a prompt. That’s not acceptable in regulated environments. CollAI inserts a deterministic sanitization boundary inside your VPC, then forwards only scrubbed JSON to the cloud.
Built for teams that can't afford downtime.
AI that investigates the moment alerts fire. Real-time state, real root cause, real suggested fixes — you stay in control.
Zero-Trust Sanitization Boundary
Three independent detection layers — deterministic regex, Shannon entropy analysis, and contextual ML — scrub payloads inside your VPC before any data leaves your network.
1-Tap Approval Workflows
Get root-cause analysis and proposed remediation scripts pushed to your phone. Nothing runs autonomously without your cryptographic sign-off. Human-in-the-loop execution with full audit trails.
Enterprise-Grade Compliance
Built for SOC 2 Type II, PCI-DSS, and HIPAA architectures. Every decision is logged, every secret is redacted, every transaction is cryptographically verified.
IaC Native Deployment
No UI config required. Deploy via Terraform to your VPC. Point your webhooks to the local agent. Everything is infrastructure-as-code, reproducible, and auditable.
Tamper-Evident Audit Trail
Each redaction produces a SHA-256 fingerprint hash-chained to the previous event. Auditors can cryptographically verify no record was altered or removed after the fact.
Purpose-Built Native Mobile
CollAI is not a thin web wrapper. The mobile app is a dedicated incident workspace for triage, approvals, and follow-up actions on the move.
Stop debugging in chat apps.
Most incident tools are glorified pagers that force you to debug inside Slack. But chat apps weren't built for 2 AM server logs, multi-file code reviews, or architecture diagrams. It's a formatting nightmare.
CollAI is a purpose-built mobile workspace.
We built a standalone, native mobile environment specifically for engineering fires.
- Native log viewer & full terminal context
- Multimodal AI for diagrams and code — no laptop required
CollAI vs. the 3 AM phone call.
Traditional on-call costs you sleep, context, and time. CollAI handles the first 90% autonomously.
| CollAI | Traditional | |
|---|---|---|
| Time to first diagnostic | < 30 seconds | 5–15 min (manual) |
| Credentials and secrets | Never sent to AI in plain text | Often in prompts or logs |
| Approve from anywhere | Push to phone, one tap | VPN, laptop, Slack |
| Who runs the fix | You approve; AI suggests (Pro: executes) | Manual runbooks only |
| On-call woken up | Only when it matters | Every page |
Built like an enterprise security product.
A clean, deterministic edge layer that gives your org AI leverage without making the LLM your new exfiltration surface.
Three-Layer Redaction
Pattern matching, mathematical entropy analysis, and contextual ML run independently inside your VPC. Evasion requires fooling all three.
Self-Adapting Detection
Flag a missed pattern and the engine learns it locally in-memory — no retrain, no cloud call, no restart. Zero-trust stays zero-trust.
Cryptographic Audit Chain
Every redaction produces a SHA-256 fingerprint chained to the previous event. Tamper with one record and the entire chain breaks.
Turn on AI diagnostics without adding risk.
Deploy the agent in minutes, point internal webhooks to `:8080`, and keep secrets inside your VPC.