1 · Detection
Events & signals
Real-time events, HTTP and job health, webhook outcomes, anomaly rules — surfaced where operators already look.
Consulting lane · High-ticket infrastructure
AI Self-Healing &
Debugging Layer
For legacy code, long-lived backends, and busy SaaS stacks where incidents cost revenue — not demos that never break.
“We don't replace your system. We help it survive incidents with clear loops, limits, and evidence.”
CTO-credible framing: execution + monitoring + AI-assisted recovery inside governance — never “the model rewires prod alone.”
What you are actually buying
Not a vague “self-learning organism.” A designed reliability loop: detect failure modes early, shorten time-to-diagnosis with AI-assisted triage, run only allow-listed recovery, record outcomes so the next incident is cheaper — with humans on the escalation path until you deliberately promote automation.
- Alerts tied to billing, execution, HTTP, jobs — wired to observability patterns you already use or we add.
- Diagnosis proposes structured hypotheses + confidence — operators approve or reject.
- Recovery is enumerated (retry webhook, degraded mode, route fallback, isolate layer) — not open-ended patching.
- Every suggested or executed step leaves an audit trace suitable for scrutiny.
Honest positioning: your system already encounters failures — we shorten MTTR within bounds CTOs sign off on.
Architecture
Five layers buyers can defend in a procurement call
Aligned with stacks we ship: Workers, KV, Stripe paths, dashboards — not generic cloud slides.
2 · Diagnosis (AI-assisted)
From noise to hypotheses
LLM summarizes logs/state into actionable classes — bounded output, citations to sources, reviewer gate. Example shape:
{"issue":"Webhook signature mismatch",
"risk":"Revenue loss",
"confidence":0.91,
"fix_suggestion":"Verify STRIPE_WEBHOOK_SECRET vs dashboard"}
3 · Recovery (controlled)
Allow-list execution
Retries, safe reroutes, disable broken subsystem, Stripe-safe replay queues — promoted only after playbook sign-off.
4 · Incident memory
“Learning” without mysticism
Store pattern → resolution → outcome. Future runs get auto-suggest + alert, not silent self-rewrite.
5 · Governance
No full AI control plane
Actions are logged, rate-limited, and tiered by risk class. Approval paths and kill switches stay first-class — what separates enterprise infrastructure from “agent startups” that skip audit.
Deep technical layering, control plane linkage, and hard boundaries: architectural memorandum →
How we usually package it
Figures are directional scoping bands — signed SOW maps to stack surface area and compliance posture.
Who should see this offer
Upsell ladder
- After audit: “Your posture is brittle under load / revenue paths.”
- After report: “Here's exactly what broke and what we'd tighten.”
- Close: “We can remediate manually — or ship the layer so recovery is repeatable.” ← €15K+ decision point.