$723B
Cloud operations surface
Gartner forecasts worldwide public cloud end-user spending at $723.4B in 2025.
incident replay / productionboot sequence
autonomous self-healing devops engineer
DevPilot AI
Detect. Diagnose. Fix. Heal.
A premium AI operations cockpit that turns Kubernetes alerts, failed deployments, Terraform drift, and incident memory into human-approved recovery actions.
devpilot.boot
> I
_live incident feed
Infrastructure alerts
CrashLoopBackOff detected
00:01production/devpilot-api restart count crossed threshold
ai root cause engine
Analysis stream
Root cause
DATABASE_URL missing
Blast radius
API pods, checkout path
Recovery plan
Rollback + config patch
DevPilot cockpitmonitoring
recovery.plan.ts
kubectl rollout undo deployment/devpilot-api -n production
patch configmap devpilot-api-config --from approved-plan
verify /ready -> 200 OK
write incident memory -> recoveredapproval gate
human review required
health probe
/ready returned 200 OK
incident memory
recovery saved to timeline
TAM
A large cloud operations market is being pulled toward AI-native remediation.
DevPilot starts with the urgent wedge: every cloud-native team already pays for observability, incident management, infrastructure tooling, and engineer time. The expansion path is broader operations automation across reliability, cost, security, and governance.
$487B
AI infrastructure pull
IDC projects AI infrastructure spending will reach $487B in 2026.
79%
AI incident adoption signal
Atlassian reports most teams are already exploring AI for incident trending.
Problem
DevOps teams have dashboards everywhere and accountable recovery nowhere.
Incidents are still manual
Engineers jump between alerts, logs, dashboards, cloud consoles, tickets, and chat while customer impact keeps compounding.
Runbooks stop at advice
Most tools explain what might be wrong, but they do not turn diagnosis into reviewed Terraform, Kubernetes, and pull-request actions.
Leadership cannot see recovery ROI
Reliability spend is hard to justify when the team cannot connect incidents, saved engineer hours, avoided downtime, and customer risk.
Solution
One AI control loop for the moments when production is on fire.
DevPilot does not replace engineers. It compresses the work between signal and safe action, then leaves an auditable record for the team.
Incident memory and analyticsKubernetes restart and rollbackTerraform remediationCloud cost optimizationSecurity analysisSaaS billing and usage metering
Detect
Listen to logs, CI/CD events, Kubernetes health, drift, cost, and security signals.
Diagnose
Rank likely root causes with incident memory and explain the active failure.
Fix
Generate remediation files, Terraform patches, PRs, and infra commands.
Heal
Apply approved recovery actions, verify results, and store the audit trail.
ROI
The payback story is simple: reduce MTTR, recover engineer focus, and avoid one painful outage.
The model below is illustrative, but the buyer logic is familiar: incident work is expensive because it burns senior engineering time while revenue, productivity, and reputation are at risk.
$22.5K
monthly engineering time recovered
20 incidents x 45 minutes saved x 5 engineers x $150 blended hourly cost.
1 hour
prevented downtime can fund a year
A single avoided outage hour can exceed the annual cost of an early team plan.
250
monthly recovery actions in Pro
Quota aligned to incident response, auto-heal, and remediation workflow usage.
Pricing
Start self-serve, expand into enterprise operations.
Free
For individual founders, local proof of concept, and early production evaluation.
$0/mo
250 API requests
25 AI actions
5 recovery actions
1 team member
Pro
For teams validating incident recovery automation with real usage.
$49/mo
10,000 API requests
1,000 AI actions
250 recovery actions
5 team members
Enterprise
For production SRE teams that need governance, scale, and procurement support.
Custom
Custom quotas
SSO and audit controls
VPC or private deploy
Priority support
Pilot pipeline
Capture real buyer interest directly from the live product.
DevPilot now has a production lead path: visitors can request pilot access, the backend stores the signal, and the monitoring dashboard counts it as real user traction.
Live Vercel frontend
Render API with Postgres readiness
CI, E2E, and smoke checks
Pilot lead capture pipeline
Testimonials
Representative buyer feedback from the pilot narrative.
"DevPilot gives our incident review a missing piece: the proposed fix, the approval trail, and the ROI story in one place."
VP Engineering
Series A fintech platform
"The product clicked because it did not stop at charts. It moved from failure signal to a reviewed recovery action."
Platform Lead
Cloud-native health tech
"This is the kind of AI workflow we would trust first: human-approved, infrastructure-aware, and measurable."
SRE Manager
B2B SaaS infrastructure team
Startup-ready investor story
Built as a working product surface, not a slide-only pitch.
Market notes reference Gartner public cloud spending, IDC AI infrastructure spending, Atlassian AI incident-management research, and downtime-cost benchmarks from Atlassian and ITIC.