AI Rescue
Your last AI project failed—often due to poor integration, wrong problem selection, or no adoption plan, not because AI doesn't work. We audit what broke, separate tech issues from adoption issues, salvage what we can, and get you live again. No blame—just a fix.
Implementation Cycle
Audit
Code review, integration check, and user adoption interviews. We identify why it failed—wrong problem, poor integration, or no adoption.
Go/No-Go
We tell you clearly: fixable in place or needs a rebuild. No sugar-coating; you get a recommendation and a fixed-price path.
Remediation
We fix integrations, retrain or replace models, add guardrails, and align the solution with how your team actually works.
Relaunch
Redeployment, monitoring, and adoption plan. You go live with clear success metrics and support.
What you get
Full audit of existing implementation (code, integrations, data)
Root cause analysis: tech vs adoption vs wrong problem
Salvage assessment: fix in place vs rebuild
Remediation plan and implementation
Team retraining and adoption plan
Relaunch with monitoring and success metrics
Common Failures We Fix
Chatbot Nobody Uses
Retrain on your actual data, add guardrails, and align with real workflows so the team adopts it.
Integration Broke
Rebuild the API handshake, add error handling, and validate with your live systems.
Too Slow
Optimize pipeline and switch to faster models (e.g. Groq, Haiku) without losing accuracy.
Vendor Ghosted
Reverse engineer the code, document everything, and either maintain in-house or hand off cleanly.
Wrong Problem Selected
Re-scope to a high-ROI use case from our audit and rebuild with clear success metrics.
No Adoption / Too Complicated
Simplify the workflow, retrain the team on real use cases, and build adoption into the process.
Ready to start?
Book a free 30-minute assessment to discuss your specific requirements.