AI-native systems for private equity and the mid-market

Stop starting over.

Lapis turns what your organization already knows into working systems — and makes them smarter with every use. Modernize operations in weeks, not years, without big-company overhead.

Book a 90-minute proof of valueSee the results

The Lapis Story

Organizations keep losing what they know.

Every company we meet has the same hidden problem: its most valuable knowledge — how things actually work, why decisions were made, where the risks really sit — lives in a few people's heads and a pile of stale documents. When those people leave, or a new team arrives, the organization starts over. Again.

Our founder spent more than 30 years inside some of the world's largest technology companies, leading modernization programs and inventing the methods teams still use to untangle complex systems. The methods worked. The understanding still evaporated.

Lapis is the answer he wanted for his whole career: an AI-native engine that captures how your business really runs, keeps it current, and uses it to build and run systems. Knowledge compounds instead of resetting.

The question isn't “how do we go faster?” It's “how do we stop starting over?”

How we work

One engine. Two ways to put it to work.

01

Lapis Platform

Your business knowledge, made operational

Lapis connects to the documents, meetings, code, and systems you already have, and builds a living map of how your business actually operates. On top of that map, it automates the work — analysis, specifications, integrations, reporting — with governance and a human in the loop. Every engagement makes the next one faster.

  • Understand the as-is before you spend on the to-be
  • Automate high-value workflows with full auditability
  • Knowledge that stays when people move on
02

Lapis Studio

Business applications, built in weeks

Studio is where we build with you. Describe what the business needs in plain language; Lapis Studio designs, builds, and delivers a working, deployable application — frontend, backend, data, and intelligent workflows — using Lapis as the engine. For partners and domain experts, we co-build and co-invest, turning deep industry know-how into focused software products.

  • From business idea to deployed application
  • Built on a proven, governed engine — not a one-off
  • Joint-venture model for domain experts and operators
168×
faster rebuild of a legacy claims-intake process — six weeks to six hours
2 days
from a PDF and one meeting to a working integration, versus 6–10 weeks
1 engineer
delivering the output of a 6–8 person team: 189 commits in 32 days
3 days
to give a top-tier software team the connected knowledge base it couldn't build alone

Who it's for

Built for private equity and the mid-market.

For organizations that need to modernize but don't want a seven-figure program to do it.

For private equity

Diligence the tech, not just the numbers

Map a target's systems and key-person risk before you close.

Accelerate the value-creation plan

Modernize operations inside the first 100 days.

Compound across the portfolio

What Lapis learns at one company becomes the playbook for the next.

For mid-sized companies

Big-company capability, without the big-company program

No army of consultants. No multi-year roadmap.

Retire fragile legacy processes

Replace them without losing the business rules they quietly encode.

End key-person risk

Critical know-how is captured, governed, and shared.

Results

Not a percentage improvement. A category shift.

Claims processing

A national fleet-claims processor

Its core claims intake ran on tooling deprecated in 2007, took six weeks to build, and had been built twice by two teams. Neither version could onboard a new client. Lapis reimagined it as one provider-agnostic framework in six hours. The next client is a configuration change, not a project.

6 weeks → 6 hours

Enterprise integration

A partner integration, from a standing start

No user stories, no analysis, no architecture — just a PDF and one kickoff meeting. Lapis turned the meeting into project memory, derived the data mapping, documented every design decision, and delivered a working multi-service integration in about two days.

6–10 weeks → 2 days

Software & logistics

WMSone, a warehouse-management software company

A top-tier engineering team had already invested heavily in AI coding assistants and still hit a ceiling: knowledge scattered across files, outputs that evaporated, one person on the critical path of nearly every release. In three working days Lapis gave them the connected knowledge base that discipline alone couldn't, then delivered their first roadmap build in nine working days against an 8–10 week estimate. Read the case study →

3 days to insight · 9 to delivery

Client names withheld at their request; WMSone is a pseudonym. Results reflect specific engagements.

How we engage

Start small. Prove it. Compound it.

  1. 1

    Ignite

    Start with a 90-minute proof of value on your own material, then a first deployment with quick, measurable wins.

  2. 2

    Accelerate

    Expand to more use cases and teams. The map of your business grows richer, and every project gets faster.

  3. 3

    Transform

    Lapis becomes the engine your operation runs on — across the company, or across the portfolio.

What we believe

Outcomes, not tooling

We start with how your business wants to work, not with the latest technology.

Knowledge that compounds

Every engagement leaves you smarter — not more dependent.

Governed by design

Audit trails, human approval, and your data stays yours.

Works with what you have

Microsoft 365, Google Workspace, Azure DevOps, Jira, GitLab, GitHub, your databases — and 50+ more.

Insights

Thinking out loud.

Essays, research and field notes on AI, organizational knowledge, and modernizing without starting over.

Case Study · September 29, 2026 · 9 min

WMSone: When a Great AI Practice Hits Its Ceiling

A top-tier engineering team had already invested heavily in AI coding tools, and still wasn't moving the needle. What we found in three days, and what we shipped in nine.

Read →

Essay · September 15, 2026 · 6 min

How Do We Stop Starting Over?

Thirty years of watching organizations lose their own knowledge, and why the real question for AI isn't "how do we go faster?"

Read →

Essay · September 8, 2026 · 8 min

The Exponential Value, Combinatorial Cost Race

The AI industry sells exponential value. Nobody has shown that the cost of extracting it safely, at real organizational scale, is anything but combinatorial.

Read →

All insights →

Let's find out what your organization already knows.

Bring a real problem. In 90 minutes we'll show you what Lapis does with it.

Talk to us →