In-app development + Self-healing builds + Complete observability.
The first platform where AI builds features, fixes production failures, and learns from every mistake.
Revolutionary products in one platform
Auto-fix success rate (production-tested)
Average time to fix production failure
Market opportunity at scale
All costing millions in lost revenue and customer churn
Context switching kills productivity
Features take weeks
Tribal knowledge in developers' heads
Cost per enterprise feature
3am production outages
Hours to diagnose and fix
Manual rollbacks and reverts
Avg cost per major outage
AI costs are opaque
Can't track what AI is doing
No ROI visibility for AI tools
Of AI spend is wasted
Developer productivity
Average downtime per incident
Annual cost for mid-size company
Build features from inside your application. No IDE needed.
TypeScript AST parsing detects classes, interfaces, type-only imports, dynamic imports, and React hooks. Production-grade code intelligence.
Follows imports up to 3 levels deep, understands your architecture, loads related files. Context-aware generation that knows your codebase.
7 JSON files store patterns, mistakes, rules, standards. AI learns from every fix. Never makes the same error twice.
TypeScript syntax → ESLint auto-fix → Import verification → Duplicate detection. Code that passes CI from day one.
Faster feature development
First-time validation pass rate
Annual savings per team
Automatic fixes when Vercel builds fail. Zero human intervention.
Vercel deployment fails. TypeScript error in production code.
Webhook fires within 1 second. Build logs fetched from Vercel API.
Diagnostic → Git history → Trivial revert check → Model selection → Validation → Learning
Fix committed to new branch. PR opened automatically. New build starts.
Build succeeds. Downtime minimized. Team notified.
Success rate
Max attempts
Avg cost
Uptime improvement
Average resolution time
Annual savings from prevented outages
Real-time dashboard tracking every AI call, token, and dollar.
Every API call logged with model, tokens, cost, and result. Complete visibility into AI usage.
All data isolated by organization. Complete multi-tenant security with Redis namespacing.
Expandable timeline showing build failures, auto-fix attempts, models used, costs, and PRs created.
7-day trends, model distribution, ROI tracking, and savings calculations from git reverts.
AI cost transparency
Cost and usage tracking
Proven value demonstration
Built for scale, security, and reliability
Professional developers worldwide
Total addressable market (AI development tools)
Annual savings per enterprise customer
Reduction in development costs
Per developer pricing
Enterprise team pricing
Projected retention rate
BuildFix is production-ready. 6 phases complete. Multi-tenant architecture. Real customer validation.
Production-tested code
97% auto-fix success rate
Multi-tenant architecture
Let's discuss how BuildFix accelerates your AI development strategy.
Available for meetings • Full technical deep-dive ready • Customer references available
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