Programs rarely fail without warning. The warning just isn't in the RAG.
of business transformations fall short of their original ambition.
average budget overrun on large IT projects, which deliver 56% less value than planned.
of projects are delivered successfully: on time, on budget and meeting their original goal.

Until now, a program review meant a small team, a sample of documents and a handful of interviews. AI changes that. Our AI workforce reads everything and hears everyone. An experienced human partner, who has run large programs, decides what it means and owns the results.
No one has time to read a year of reports, plans and logs side by side. Our AI workforce does, and it looks at more than 700 factors to assess your project's health.
Every status report, plan version, RAID log and set of minutes since day one. Not a sample.
Everyone who matters, from the sponsor to the front line, is interviewed, written up and compared.
Someone who has run large programs decides what the evidence means, and what to fix first.

Agree the scope and the questions that matter. Get access to documents, delivery tools and the people we need.

We read every status report, steering pack, plan version, RAID log and set of minutes. Our AI interviews the people doing the work. Everything is tested against over 700 indicators of program success and twelve green-to-red patterns.

We walk you through what we found and suggested next steps.
This is what an AI-native workforce looks like in practice. Work a traditional review team would do one step at a time runs in parallel and around the clock. The AI Director plans the work, launches the agents in parallel, sequences what depends on what, remembers every document and conversation, and keeps a full audit trail. It reports to a human partner every day, who owns every finding.

Beside your reported RAG, period by period.
Assessment of twelve common patterns that turn projects from green to red.
From 0 to 100: how far your reporting can be relied on.
Across 13 dimensions, with the weakest links named.
What happens if you run one, three or six months late.
Quick wins and potential next steps
The test draws on a library of over 700 indicators of program success, built from 35 years of experience in large project delivery. Hapsicle's AI workforce does the reading, research and cross-checking. A human partner who has run large programs owns every judgement.

Copyright © 2026 Hapsicle - All Rights Reserved.
Website content: 40% AI with the rest human.