Strategic Recon
Find where AI creates meaningful leverage.
Goals, friction, stack, data, constraints — and what already failed.
Operator-led AI execution
Endurance is the operator-led AI execution firm for leaders with serious outcomes at stake. Strategy through deployment — one small, senior team that ships.
Active engagements with Fortune 500 enterprises — built for the mid-market
The Problem
Your smartest people are experimenting. The consultants delivered a deck. The board wants a date. And nothing — nothing — is in production.
It was never a technology problem.
Without a forcing function, adoption stalls before it starts.
Fragmented, dirty data makes even the strongest models useless.
When it's everyone's job, it's no one's. Initiatives drift.
Buying software isn't a strategy. Tools without new workflow change nothing.
The build is the easy part. Changing how people work isn't.
Key strategic employees deliver and leave. Nobody inside can scale what's left.
These are execution problems. Not technology problems.
We close the gap between ambition and execution.
The Difference
Consultants advise.
Integrators implement.
Enterprise vendors sell one-size software.
Operators ship.
Software that fits you. Strategy, architecture and engineering in one senior team.
The same platform sold to everyone
Infrastructure built around your operation
You adapt to their software
The software adapts to you
Dozens in the room, none who ship
Senior operators, end-to-end
Recommendations deck
Working system in production
Generic model, generic outputs
A private brain on your proprietary data
A probabilistic black box
Deterministic, traceable to your source of truth
Avoids regulated industries
Built for them
Generalist consultants
AI engineers who ship
The Core
Deep experience building world-class large language models sits at the core of the company. We use them to build deterministic software — systems anchored to your sources of truth, not invented logic.
Every meeting, document, drawing, invoice and thread — pulled from the systems you already run.
Weighted scoring files each item to the right project, deal or job automatically.
A structured workspace, not a document graveyard. Projects, areas, resources, archives.
Progressive context: the lean picture first, the deep detail only when the work needs it.
The agent reasons, calls your tools, checks its work, and repeats — inside your permissions.
Ask twice, get the same answer. We use LLMs to build software that behaves predictably — not software that guesses.
Every output traces back to your systems of record. No invented logic, no confident fiction.
Not a chatbot bolted onto a database. The model is the operating layer.
Tiered loading keeps answers sharp. Dumping everything in degrades them.
Workflows are plain, readable files. Your team extends them without us.
The brain reaches only what each person is already allowed to see.
What We Do
Roadmaps tied to outcomes. Leverage points, priorities, operating model, governance.
Systems that kill bottlenecks: document-heavy work, customer ops, decision support.
Infrastructure that holds up in production: data, retrieval, orchestration, safety.
Your team owns it after we leave: training, playbooks, governance.
Stalled efforts diagnosed, rescoped, and relaunched on a realistic path.
How We Work
Find where AI creates meaningful leverage.
Goals, friction, stack, data, constraints — and what already failed.
Move from vague ambition to a clear, executable path.
Priorities, success criteria, scope, sequence, architecture.
Visible operational progress.
Prototypes, data pipelines, automations and integrations — live.
Durable execution. Not a demo.
Workflow refinement, training, governance, monitoring, adoption.
Capability, not dependency.
Documentation, operating rhythms, ownership handover, roadmap.
Built in the field
Not a product you adopt. Systems built around how you already run — operations, finance, revenue, workforce, reporting.
Budgets built by hand. Forecasts stale on arrival. Margin gone before anyone sees it.
A brain-powered operating system for the whole company — automated budgeting, forecasting and accounting as the financial bedrock everything else runs on.
Underwriting by hand. Investor reporting rebuilt from scratch every quarter.
An autonomous brain-powered operating system running the entire firm — underwriting through capital markets and everything investors ever see.
Expertise locked in a few partners. Realization leaking everywhere.
A brain over the firm's entire corpus, running the practice from intake through collections.
Margin per load stays invisible until long after settlement.
One operating system from tender to cash, with margin visible on every load in real time.
Every location its own island. Group P&L always arrives too late.
One operating system across every location — unit-level labor through consolidated group reporting.
Commission math by hand. Slow, opaque, impossible to audit.
A penny-accurate commissions and settlement system finance can stand behind, wired into everything upstream.
One private brain on your data, extended across every function that runs on it.
Client names held in confidence. Full detail under NDA.
Field Results
20 engineers. 1 year.
→ 2 weeks.
A team at a major Fortune 500 travel company had been working on a specific problem for a year. We solved it in two weeks. That pattern has held across every major engagement since.
6 months of waiting.
→ 4 days.
A CEO had been waiting six months for his own team to deliver an agentic e-commerce experience. We built it in four days. He's now using it to open doors at Fortune 500 retailers and financial institutions.
Regulated industries.
→ Production-ready.
Most AI firms quietly avoid regulated environments: pharma, financial services, healthcare. We don't. We've built production AI systems inside them, where breaking things is not an option and compliance is not a suggestion.
Active engagements with Fortune 500 enterprises. Details shared under NDA.
Why Now
OpenAI announced a $4 billion fund for AI implementation, partnering with Bain, McKinsey, and Goldman Sachs. Anthropic announced $2.5 billion for the same purpose. The capital is there. It is buying the same playbook, delivered to every large enterprise at once.
Standard implementation gets you what your competitors get. Infrastructure built around your own operation is the only part nobody can hand them. That is what we build, and the window to build it first is open now.
$4B
OpenAI implementation fund
Partnering with Bain, McKinsey & Goldman
$2.5B
Anthropic implementation fund
Same directive. The same playbook for everyone.
Organizations that move in the next 18 months will build a compounding advantage their competitors cannot close. The ones that wait will pay three times the price to the same firms.
Who We Help
Law, wealth, accounting. Knowledge systems and leverage, without losing the client relationship.
Modernizing operations with disconnected data and no internal AI bench.
Build-versus-buy under time pressure, without piling up technical debt.
Transformation that needs outside execution when internal-only stalls.
Not a fit for
Generic experimentation. Lowest-cost vendors. Software shopping. Anyone without executive sponsorship or the will to move.
Start Here
A dominant misconception paralyzes capable leadership teams: that AI deployment requires a massive enterprise transformation. Months of planning. Millions in investment. Everything disrupted at once.
This belief is false, and it costs real money. AI can be as simple as a walk after dinner. Small. Low-risk. High-value. Something you do this week.
The operating system comes later. This is how you find out what is worth building — before anyone writes a line of it.
Not ready for a full engagement? This is how most of ours start.
The AI Audit
$999
Flat fee. One engagement. No retainer.
Most companies spending on AI without this are guessing.
Book an AI Audit →The Team
AI engineering, enterprise architecture, and operational execution in regulated environments.
CEO & Co-Founder
Three-time startup founder and angel investor. Started in AI with Tetration and Cisco in 2018. Chief Product Officer of Prospera, an AI wealth management startup.
CTO & Co-Founder
Computer Science, Cornell. Three-time startup founder — exited his last, Tala, to Intuit.
COO & Co-Founder
UC Berkeley Haas School of Business. Wells Fargo, then Principal for a real estate investment group. Leads operations, finance and AI strategy.
CMO & Co-Founder
Indiana University. VP of Communications for Cambridge Bank. Leads marketing, client success and partnerships.
We are operators. Built for initiatives too important to drift.
Questions
Weeks to a few months, scoped into fixed deliverables — not open-ended retainers. A focused discovery first, then straight into building.
Large organizations in demanding, often regulated industries: construction, legal, capital markets, logistics, multi-unit operations. Infrastructure that has to work in production, not on a slide.
They produce recommendations. We produce systems. Strategy and build in the same engagement, by one senior team — and an order of magnitude faster.
Yes. Our best engagements run alongside internal teams — for stalled initiatives, architecture decisions needing outside eyes, or when speed outruns capacity.
Inside your Slack, your standups, your codebase. Not at arm's length. Nothing waits on a weekly status call.
No. We've shipped production AI inside pharma, financial services, healthcare and insurance — within compliance constraints, without sacrificing the outcome.
That's what the AI Audit is for. A focused diagnostic that returns a prioritized plan for where custom infrastructure pays — and where it doesn't. Yours either way.
Fixed scope, flat fee. No hourly billing, no open-ended retainers. The AI Audit is $999; build engagements are priced to the system, then delivered.
Still have questions?
Ready?
A briefing, not a sales call. Tell us what you’re trying to do — we’ll tell you if we fit.