Strategic Recon
Find where AI creates meaningful leverage.
Understanding the real situation: goals, friction points, technology stack, data landscape, constraints, and previous attempts.
Operator-led AI execution
Some initiatives cannot afford to fail.
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
Fortune 500 engagements2-week turnaroundsRegulated industriesStrategy through deploymentNo discovery theaterAI Audit · $999 flatEmbedded engineersShips, not decksMid-market focusFixed scope. Flat fee.
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.
Most AI transformations fail for predictable reasons
01
Organizational inertia.
Teams default to familiar workflows. Without a forcing function, adoption stalls before it starts.
02
Weak data foundations.
AI is only as good as the data feeding it. Fragmented systems and dirty data make even strong models useless.
03
No clear ownership.
When AI is everyone's job, it's no one's job. Initiatives drift without a single accountable driver.
04
Tool-first thinking.
Buying software is not a strategy. Deploying tools without redesigning the workflow around them changes nothing.
05
Poor change management.
The technical build is the easy part. Getting people to actually change how they work is where most initiatives die.
06
Lack of internal capability.
External vendors deliver and leave. Without building internal knowledge, organizations can't maintain or scale what was built.
These are execution problems. Not technology problems.
Endurance was built to close the gap between ambition and execution.
The Difference
Consultants advise.
Integrators implement.
Vendors sell.
Operators ship.
Strategy, architecture, engineering, and execution — combined in one small, senior team.
The old model, versus ours.
The old modelEndurance
6-month discovery phase
Audit delivered in one week
Dozens in the room, none who ship
3 senior operators, end-to-end
Recommendations deck
Working system in production
Hourly billing, open retainer
Fixed scope, flat fee
Avoids regulated industries
Built for them
Generalist consultants
AI engineers who ship
What We Do
Five areas of work. One goal: execution.
01
AI Strategy & Leadership
Practical AI roadmaps tied directly to business outcomes. Identifying leverage points, prioritizing high-impact opportunities, defining operating models, and establishing governance.
02
Automation & Workflow Transformation
Systems that eliminate bottlenecks and improve throughput. Workflow automation, document-heavy processes, customer operations, internal knowledge systems, decision-support.
03
Architecture & Operating Layer
Infrastructure for AI systems to work reliably inside real organizations. Data integration, retrieval, orchestration, model selection, safety, and iteration loops.
04
Internal Capability Building
Building the internal capability to sustain the work. Leadership education, team design, governance structures, internal playbooks, and tooling.
05
Initiative Recovery
Diagnosing and relaunching stalled or failed AI efforts. Root cause analysis, identifying salvageable assets, resetting scope, and relaunching with a realistic execution path.
How We Work
Five phases. Real outcomes.
Mission Definition
Move from vague ambition to a clear, executable path.
Selecting priority opportunities, defining success criteria, clarifying scope, sequencing the work, and identifying architecture needs.
Rapid Deployment
Visible operational progress.
Building and deploying initial systems: prototypes, data pipelines, automations, AI-assisted workflows, orchestration logic, integrations.
Embedding
Durable execution. Not a demo.
Making the system work inside the organization: workflow refinement, training, governance, monitoring, feedback loops, and adoption support.
Capability Transfer
Capability, not dependency.
Internal enablement, documentation, operating rhythms, ownership transition, and roadmap extension so the work sustains itself.
Phase 01 — ReconPhase 05 — Transfer
Field Results
Results, not presentations.
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
The window is open. For about 18 months.
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. For the next 12 to 18 months, every frontier lab will focus almost entirely on Fortune 500. The mid-market — companies doing $10M to $500M in revenue — will be mostly left to figure it out on their own.
That is our market. We are building in it now, with the experience, tools, and reputation to serve it well. Before the big players arrive and triple the price.
$4B
OpenAI implementation fund
Partnering with Bain, McKinsey & Goldman
$2.5B
Anthropic implementation fund
Same directive. Fortune 500 focus.
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
We work with leaders. Not committees.
A
Professional Services
Law firms, wealth managers, accounting firms, and consulting firms looking for workflow leverage, knowledge systems, and AI-enabled service delivery without losing the client relationship.
B
Mid-Market Operating Companies
Organizations modernizing operations, eliminating friction, and improving scalability, often with disconnected data and limited internal AI capability to draw from.
C
Venture-Backed Companies
Founders and product teams building AI-enabled products or navigating build-versus-buy decisions. Speed matters. So does not creating long-term technical debt.
D
Large Enterprises
Complex transformation efforts that require focused outside execution capability. Situations where stakeholder complexity and organizational pace make internal-only approaches fail.
Not a fit for
Generic AI experimentation. The lowest-cost vendor. Software shopping. Organizations without executive sponsorship or those not prepared to move once a direction is chosen. We work best with leaders who are serious about outcomes.
Start Here
AI doesn’t have to be open heart surgery.
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.
Not ready for a full engagement? This is how most of ours start.
The AI Audit
$999
Flat fee. One engagement. No retainer.
- We look at what you're doing and what you're not
- We identify where AI generates real ROI, and where it's a waste of money
- You walk away with a prioritized roadmap
- Whether you work with us afterward or not
Most companies spending on AI without this are guessing.
Book an AI Audit →The Team
Built by operators.
Our backgrounds span AI engineering, enterprise architecture, product design, and operational execution across regulated, high-growth, and complex environments.
Alex Sok
Founder & CEO
Leads Endurance engagements from strategy through deployment.
Sid Bhambhani
Co-Founder & CTO
Co-founded Summatti, an AI company acquired by PartnerHero. Over 20 years of technology leadership.
Nick Maxwell
Co-Founder & Chief AI Officer
Founding engineer at TALA, acquired by Intuit. Computer Science, Cornell.
We are operators. Built to execute in environments where the initiative is too important to drift.
Questions
Answered before you have to ask.
Depends on scope. The AI Audit is one engagement: a prioritized roadmap within a week. The Embedded AI Engineer tiers run 2 weeks, 2 months, or 6 months. We scope work into defined deliverables, not open-ended retainers.
Our sweet spot is the mid-market, companies doing $10M to $500M in revenue, but we work across the full range from venture-backed startups to Fortune 500 enterprises. The common thread is leadership that's serious about outcomes and prepared to move.
Big 4 firms produce recommendations. We produce systems. Their model is analysis and advisory, delivered by large teams, with implementation handled separately. Ours is a small senior team that does both: strategy and build, in the same engagement. We're also faster by an order of magnitude and don't require six-month discovery phases.
Yes, and some of our most productive engagements are alongside internal teams, not instead of them. We're useful for initiatives that have stalled, architectural decisions that need an outside perspective, or situations where speed matters more than the team has capacity for.
It means working inside your organization: in your Slack, your standups, your codebase. Not at arm's length producing deliverables. The work moves faster because we're not waiting on weekly status calls to understand what's changed.
No. We've built production AI systems inside pharmaceuticals, financial services, healthcare, and insurance. Regulated environments require deliberation, not bravado. We build within compliance constraints without sacrificing the outcome.
That's exactly what the AI Audit is for. $999 flat fee. We look at your operations, your data, and your goals, and give you a prioritized roadmap. You walk away with clarity, whether you work with us afterward or not.
Fixed-scope engagements at flat fees. No hourly billing, no open-ended retainers unless you want them. The AI Audit is $999. Embedded AI Engineer engagements range from $19K to $179K depending on scope and timeline. We price the scope. We deliver it.
Still have questions?
Ready?
Brief us on a mission.
The first conversation is a mission briefing, not a sales call. Tell us what you’re trying to accomplish. We’ll tell you if we’re the right fit.