Promise 01
1,000 manual hours a month
AI will transform our operations.
About 1,000 manual hours a month returned to the business.
AI consulting & implementation
We find where frontier AI belongs in a business, ship it to production, and tie the result to the P&L.
Industries
Any industry. Our strength is adapting fast to a new business, which is why private equity portfolios, spanning every sector, are a natural fit.
An AI consulting firm that also writes the code: a senior team of operators and forward deployed engineers who have run data and AI inside global enterprises and built it hands-on in startups.
$300M+
in data-driven revenue, built from zero by our leadership
40+
generative-AI use cases evaluated, sequenced, and governed in six months
20 years
turning data and AI into growth, margin, and efficiency
Everyone can see what AI promises. Few can show the proof.
The gap is rarely the model. It is the distance between a boardroom ambition and a system people use on Monday morning. We close it by doing both jobs at once: setting the strategy and writing the code. Success criteria are set before the first line of code, and we stay through rollout so what ships is used.
See the four moves →Promise 02
$300M+ from zero
Our data is an asset.
Data-driven revenue built from zero to $300M+.
Promise 03
40+ use cases in six months
We have dozens of use cases.
40+ generative-AI use cases evaluated, sequenced, and governed in six months.
Promise 04
15,000 queries a second, sub-10ms
We need it in production.
15,000 queries a second at sub-10ms, live and earning.
The ledger
Outcomes delivered by our leadership across operating roles and client engagements.
We build with whichever frontier model fits the job.
Anthropic
OpenAI
Google
Meta Llama
Mistral
Open-weight models
RAG pipelines
Evaluation harnesses
Agentic workflows
MCP workflows
Data products
Reference implementations
Method
Four moves
From AI strategy to production. One accountable team. Success criteria (revenue, margin, hours reclaimed, adoption) are set before the first line of code, and we stay through rollout so the system is used, not just shipped.
The engagement, step by step →
Move 01 Diagnose
Intake with the business sponsor, then a discovery workshop: where generative AI, agents, and data products create value, and where they don’t.
Workshop
A scoped, build-ready brief, sequenced by dollar impact and risk.
Brief
Move 02 Build
A scoped brief, then a working system in a one to six week window.
Weeks
Forward deployed engineers embedded with your team: RAG pipelines, evaluation harnesses, agentic and MCP workflows.
Production
Move 03 Prove
Success criteria set before the first line of code: revenue, margin, hours reclaimed, adoption.
Criteria
We stay through rollout and hand-off so the system is used, not just shipped.
Rollout
Move 04 Compound
Every win becomes a reusable playbook and reference implementation, so the second deployment costs a fraction of the first.
Playbook
Selected work
Under NDA. Outcomes speak.
All selected work →Strategy
A unified media group for a global broadcaster
Brought data and advertising together across streaming, ad-tech, and digital divisions into a single operating group.
Investment
A league‑scale data and analytics platform
Shaped the strategy, sequencing, and build-vs-buy decisions for a major new data and analytics investment.
Build
A geospatial decision engine for connected TV
150M+ U.S. building footprints tied to viewership at 15,000 queries a second and sub-10ms lookups, opening a new line of ad spend.
Operators first, engineers always.
How we work
| Forward deployed engineering | Engineers inside your business | Our engineers sit inside your business, next to the people who own the problem. |
|---|---|---|
| Frontier models | Whichever fits the job | Anthropic, OpenAI, Google, Meta Llama, Mistral, open-weight models. |
| Technical standard | Set on every build | Orchestration, evaluation, and vector store choices, and a clear call on what stays in house and what goes to a partner. |
| Small on purpose | Scope it, build it | The people who scope the work are the people who build it. |
Case studies, not the limit
Four industries from our case studies. The method is the same in any business with data and a P&L to move. Industries →
Questions
Questions, answered.
What does Promise & Proof do?
We are an applied AI consulting and implementation firm in New York. We find where frontier AI belongs in a business, ship it to production, and tie the result to the P&L.
Who leads Promise & Proof?
The firm was founded in 2025 by a former global head of commercial data at a global media company, with 20 years turning data and AI into growth, margin, and efficiency. A senior team of operators and forward deployed engineers runs every engagement, and the people who scope the work are the people who build it.
What does an engagement look like?
Intake with the business sponsor, then a discovery workshop, then a scoped, build-ready brief sequenced by dollar impact and risk. The build runs in a one to six week window, followed by hand-off. Success criteria (revenue, margin, hours reclaimed, adoption) are set before the first line of code, and we stay through rollout so the system is used.
What is a forward deployed engineer?
A senior engineer who works inside your business to scope, build, and ship a production AI system, and stays accountable until it is used. See how forward deployed engineering works.
How is this different from a traditional AI consultancy?
We do both jobs at once: setting the strategy and writing the code. The people who scope the work are the people who build it, and success is measured in revenue, margin, hours reclaimed, and adoption, not in deliverables.
Which AI models do you work with?
Whichever frontier model fits the job: Anthropic, OpenAI, Google, Meta Llama, Mistral, and open-weight models. We set the orchestration, evaluation, and vector store choices on every build. See every lab, compared.
Which industries do you work in?
Any industry. Our strength is adapting fast to a new business: the four moves work wherever there is data and a P&L to move, which is why private equity portfolios, spanning every sector, are a natural fit. Our published case studies come from media, streaming, sport, and ad tech; they show how the work is done, not where it stops. See industries and AI value creation for private equity.
How do engagements start?
Most engagements come by referral, and a referral is not required. Tell us what you want to build on the get started page, or write to hello@promiseandproof.com.