AI Strategy & Implementation

Get Return On
your AI
investments.

Companies bolting AI onto existing processes are not seeing ROI. The ones that are rebuild around it. We identify where AI actually moves your numbers, redesign the work around it, and build the systems that do it — then help your team own it.

Approach /

AI native approach.
Business first results.

AI-native means we design around what AI can do now — agents, models, and systems built into the work, not a chatbot bolted onto the old process. Business-first means we judge all of it by your numbers: the work that gets cheaper, the revenue that opens up, the customers you couldn't reach before. We come from product, design, and engineering, so the people who spot the opportunity are the ones who build it — and we stay through go-live until it's running in production and your team owns the result.

01Assess & Architect

Find the leverage

We go through your data, tools, and workflows to find the handful of places AI actually pays off — and the ones where it's just a distraction. You get specific bets with real numbers, not a wish list.

02Build & Iterate

Build it for real

We build the working systems — agents, models, the tools your team will actually use — in tight loops. You're using real software in weeks, tuned against how the work really goes, not handed a polished demo months later.

03Implement & Adopt

Make it stick

We deploy it, retrain the people who'll own it, and change the workflow around it. We stay through the awkward first weeks until the new way is just the way things run.

Services /

Broad business perspective.
Full stack capabilities.

AI reaches every layer and every area of your organization. Our capabilities are built to match — horizontally broad across the business, vertically deep down the stack.

Find the AI bets worth making

Strategic

We dig into how your business actually makes money and find the specific spots AI changes it: work that gets cheaper, things you can now sell, revenue you couldn't reach before. You come away with the two or three moves worth making and the numbers behind them — then we go build them. No 80-slide deck that sits in a drawer.

Redesign how the work gets done

Automated

AI only pays off when the work changes around it. We rebuild the actual workflows — who does what, what the software now handles, where a person still needs to decide — so the team runs leaner instead of bolting a chatbot onto the old process.

Get your people actually using it

Adoptable

The best system dies if nobody touches it. We sit with the people who'll do the work, retrain them on the new way, and stay through the messy first weeks until the new workflow is just how things are done.

Build agents that do the work

Agentic

We build agents that run real multi-step jobs end to end — pulling from your systems, making the call, taking the action, and looping in a person only when judgment is needed. Reliability on the hundredth run, not the demo, is the part we own.

Leverage your IP & internal knowledge

Proprietary

Your contracts, docs, tickets, and transcripts are full of answers nobody can find. We turn them into something your team and your AI can ask a plain question and get a correct, sourced answer back — wired into the tools your people already use.

Run AI on your own terms

Internalized

For work that can't leave your walls, we stand up open-source and local models on your own servers or private cloud — your data never goes to a third party. The same capability without the per-seat bill or the compliance headache.

Impact /

Compound impact across
the organization.

AI creates leverage across your whole organization, not just one corner of it. These are the functions where it pays off fastest — and what we actually build for the leaders who run them.

CMO

Marketing

Agents that produce and personalize campaigns, and analytics that tie every dollar of spend to what it returned.

CFO

Finance

Models and automation behind forecasting, due diligence, and the monthly close — finance as real-time answers, not scorekeeping.

COO

Operations

We go after the highest-cost workflows first — supply chain, back-office, request routing — and compound savings every cycle.

CRO

Sales

Lead scoring, outreach, and deal intelligence that tells your team who to call, what to say, and which deals are real.

CX

Customer Service

Support agents that resolve routine tickets end to end and hand the hard ones to a person with full context.

GC

Legal & Compliance

Systems that read contracts, flag risk, and keep reviews moving — weeks of manual review turned into hours.

CTO

Technology

Internal tooling and developer-facing agents — code assistance, incident triage, and automating help-desk tickets.

CPO

Product

Research synthesis and analytics that turn scattered feedback and usage data into a clear read on what to build next.

Experience /

High stakes challenges.
Hands on experience.

Our team brings direct, hands-on experience from engagements at leading organizations across banking, healthcare, insurance, energy, private equity, consumer goods, and technology.

Bank of AmericaBanking
CitigroupBanking
GoogleTechnology
HumanaHealthcare
Kaiser PermanenteHealthcare
AIGInsurance
ChubbInsurance
BBVABanking
NissanAutomotive
Victoria's SecretRetail
Colgate-PalmoliveConsumer Goods
Xcel EnergyEnergy
ZoetisLife Sciences
J.D. PowerIntelligence
WileyPublishing
Seacoast BankBanking
GuidehouseConsulting
West MonroeConsulting
American SecuritiesPrivate Equity
THLPrivate Equity
Larga VistaReal Estate
FAQ /

Common questions about AI.

What are cloud AI models actually doing with my data?

Your prompts and data are sent to the provider's servers to generate a response. On reputable enterprise and API tiers, they don't train on your business data, and you get retention controls — including zero-retention options. We set up the right tier, contracts, and configuration so your data is handled the way your auditors require.

Should we use local models or cloud models?+

It depends on the job. Cloud models are the most capable and fastest to ship, so they're right for most work. Local or private-cloud models make sense when data can't leave your walls or you need predictable cost at high volume. Often the answer is a mix.

How do we keep our AI costs under control?+

Most runaway bills come from sending too much context and using a flagship model where a smaller one would do. We route simple tasks to cheaper models, cache, trim context, and batch — and instrument cost from day one so it never surprises you.

How do you handle mistakes and hallucinations?+

We don't ship models raw. We ground answers in your real data with sources, add checks and guardrails, keep a person in the loop where judgment matters, and log decision traces so you can see why the system did what it did.

Do we have to replace our existing software?+

No. We build into the tools your team already uses instead of ripping them out. AI usually sits on top of your current stack — connected to your data and workflows.

Will this replace our people?+

The goal is to take repetitive, low-judgment work off your team's plate. We retrain the people who'll own the new workflow and measure success by real usage — not headcount cuts.

How do we get started without betting the company on it?+

We start small and concrete — a short assessment to find the two or three places AI pays off, then a focused build you can see working in weeks. Real software and real numbers before any big commitment.

Contact /

Let's talk about how to leverage AI in your business.

We start every engagement with a conversation — no pitch decks, no pressure. Tell us what you're working on and we'll give you an honest perspective on where AI can (and can't) help.

Send us a message

Tell us about your organization and what you're working on. We'll respond personally.