Methodology first. Evidence before execution.
We build AI-readiness assessment as software instead of a consulting deliverable, then carry the same evidence forward into planning and governed delivery.
The analysis and the work never met.
The case for an AI investment and the work that delivers it usually live in different artifacts, owned by different teams. A diligence deck never learns what the migration team actually built. The migration team never sees the assumption that justified the budget. Twelve months later nobody can say whether the number was right, because the number and the outcome were never in the same system.
So we made the assessment computable. Eight deterministic scoring engines, six readiness dimensions, and Newton-Raphson IRR on modeled cash flows: the math an investment committee already expects, with every input visible on screen. Same inputs, same score, every time. Then we made that output an input: the assessment populates the value plan, the plan populates the migration queue, and the run record comes back to sit beside the projection it was meant to deliver.
None of that removes judgment. An operating partner still sets the assumptions. When a migration crosses the configured risk thresholds, a named human approves the run before execution. The reasoning and the decision survive the handoff.
What we publish
The scoring methodology, the inputs behind every number, the delivery patterns teams reuse, and implementation guides. If a figure cannot show its work, it does not ship.
Who it is for
PE operating partners underwriting AI value creation, deal teams screening targets and cohorts, and the portfolio company executives who have to run the plan afterward.
Where we are
San Francisco, remote-first. The team works directly with users on the methodology, the product, and the current limits.
How to reach us
Book a working session on the contact page, or email migrateforce@sociallabs.com for anything about the company itself.
What we have not proved yet.
The people buying this have been oversold before. Here is the part most vendors leave off their site.
We are pre-revenue and in beta
There is no wall of fifty enterprise case studies, and we are not going to manufacture one. Beta access is free because the product is still earning its price.
The full loop has not run its course
The product can link underwriting, execution, and realized outcomes. It has not yet run across a portfolio for the 18 months needed to test whether measured outcomes improve the next underwriting decision. That is the thesis; it is not evidence.
Code generation is commodity, and we know it
Turning an OpenAPI spec into an MCP server is not a moat. Composio, Speakeasy, and open-source tooling do it. The part we think is hard to copy is the Skills layer that tells an agent why and how a migration is done, not just which endpoints exist.
We orchestrate above the execution layer
Our scenario math is decision support, not accounting. Our generated integrations connect to your billing, ERP, CRM, and compliance systems. Those systems remain the systems of record.