Evidence-first enterprise AI
Most enterprises are paying for AI. Far fewer are getting paid back.
Second Foundation exists to put you in the second group. We find where AI moves your P&L and prove it with short, measured engagements. When the evidence says stop, we say stop.
Our team has delivered for
- Global cybersecurity platforms
- Payments networks
- Enterprise data infrastructure
- Specialty lenders
- Compliance software
The record
What this team has delivered.
Our team delivered this work across 13+ years and ~38 enterprise accounts, under a practice certified to ISO/IEC 27001, ISO 9001, and SOC 2 Type II. Ask for references and we'll make the introduction.
We measured every figure from the delivered engagement and state its basis. Three case studies below carry the full detail, tools and boundaries included.
Start here
Book a free AI Value Session.
Ninety minutes with our senior team. We look at where your AI investment sits today across tools, pilots and platforms, then give you a straight read.
What you leave with:
- A prioritized read on where the evidence says value is reachable.
- The risks sitting in what you've already deployed.
- Where it fits: a proposal for a short, fixed-scope evidence assessment.
If we don't see a case, we'll say so and point you somewhere better. We'd rather walk than stretch a thesis.
Case studies
Proof, with the basis for each claim.
Anonymized engagements our team delivered, sized against public industry research rather than named clients. Each one shows the problem, what we built, the measured outcome, and the boundary of the claim.
Insurance-document automation for a specialty franchise lender
Proof-of-insurance verification cut from hours to under 30 minutes, with full audit lineage on every extraction.
Read the case study →Legacy platform modernization for a mid-market compliance software provider
A decade-old SOAP/WCF platform moved to REST APIs without taking live enterprise customers offline.
Read the case study →Test-automation acceleration for a restaurant guest-engagement platform
Days-long manual regression cycles replaced by a self-healing automation suite that runs in minutes.
Read the case study →The operating model
From first touch to renewal, on one operating model.
Most AI programs stop at one function. This is the whole value chain: what agents run, what a human signs off, the evidence each stage leaves behind, and the number that stage owns. Retention feeds demand, so the loop closes.
| Demand | Sales | Build | Onboard | Retain | Operate | |
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| Handoff in | ↺ Proof and unit economics | Qualified intent | Signed scope | Release and runbook | Adoption baseline | Usage profile |
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| Moves the number |
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Hover a stage to trace it. Scroll sideways for the full chain.
Delivered so far across engineering, document operations and revenue retention. The rest of the map is where the same method applies.
Observed on delivered engagements: 6.7× delivery throughput and ~50% reduction in code-analysis effort on a legacy modernization program, with 60–80% of implementation AI-assisted and developers reviewing every generated change. Read that case study.
Who we are
The team behind the record.
Second Foundation AI is built and run by senior operators from a 13-year enterprise software practice serving ~38 active enterprise accounts. The same people delivered the work in the case studies below.
We run Second Foundation on the model we build for clients: agents execute, humans own judgment, every claim carries instrumentation. What we learn, we publish in the build log.
- Enterprise delivery13+ years
- Active enterprise accounts~38
- Claude-trained engineers22
- Claude-certified architects4
- ISO/IEC 27001
- ISO 9001
- SOC 2 Type II
Mission & method
Discover what becomes possible when organizations are AI-first.
We pursue consequential problems where autonomous intelligence creates better ways of working. We build the technologies and operating models that make them real, then turn validated discoveries into reusable capabilities, products and businesses.
We run it like a research lab: hypotheses, cheap experiments, measured evidence, kill or continue. We concentrate resources where results justify them. We want to discover how organizations themselves should work when intelligence, execution and coordination can be autonomous.