Forward-deployed engineering
AI transformation, from inside the work.
Estate Grown embeds forward-deployed engineers in your teams. They learn how the work actually moves, build AI into the systems you already run, and stay until the gains compound. Then they hand you the keys.
- Engineers embedded in your teams
- Built in your cloud, under your controls
- You own every line we write
- Measured against a baseline
I / Why AI stalls
Most AI stalls between the demo and the work.
Pilots are built beside the business rather than inside it: on clean data, judged by demos, and handed to teams who were never asked. They impress in the boardroom and wilt on the floor.
The forward-deployed model reverses the order. The engineer goes to the work first, learns how it actually moves, and the software follows what they find. Nothing ships without a baseline to beat and an owner on your side.
II / The graft
New growth on old roots.
A vineyard need not replant to change what it grows. It can graft.
A new variety is set onto rootstock that took decades to establish, and the vineyard keeps its roots. AI transformation works best the same way: new capability joined to the systems, data, and people you already trust.
i. The scion
New capability (agents, assistants, and automations) chosen for the work rather than for the headlines.
ii. The union
Forward-deployed engineers. A graft only takes where someone tends the join, so ours work inside your teams, where the new meets the established.
iii. The rootstock
Your systems, data, and people. Proven, kept, and built upon, never ripped out and replanted.
iv. The fruit
What gets measured: hours returned, errors avoided, and revenue moved, against a baseline set before we build.
III / The model
An engineer who works where the work is.
A forward-deployed engineer is a software engineer who works inside a client’s operation rather than at a distance from it: in your channels, your systems, and your stand-ups. The model was proven by teams deploying software into demanding environments. We bring it to operating companies, and staff every engagement as a small pod.
A partner
Owns the outcome and the relationship from the first conversation to the handover. You will have their number.
An operator lead
Has run teams like yours, and translates how the work actually moves into what the software must do.
Forward-deployed engineers
One to three, embedded in your channels, your stand-ups, and your systems, building where the work happens.
How it differs from what you have tried.
| Question | A strategy consultancy | A software vendor | Forward-deployed engineering |
|---|---|---|---|
| Who shows up | Partners at the pitch, analysts after | An account team, then a support queue | Engineers and an operator lead, inside your team |
| What you receive | Recommendations | Licenses and a roadmap | Working systems in production |
| Where it runs | In a slide deck | In the vendor’s cloud | In your cloud, under your controls |
| Who owns it | You own the deck | The vendor owns the platform | You own the code, prompts, evaluations, any models trained for you, and documentation |
| How it is judged | Delivered on schedule | Seats activated | Hours returned, errors avoided, and revenue moved, against a baseline |
| When it ends | When the report is accepted | When you stop paying | When your team can run it without us |
Forward-deployed engineering
- Who shows up
- Engineers and an operator lead, inside your team
- What you receive
- Working systems in production
- Where it runs
- In your cloud, under your controls
- Who owns it
- You own the code, prompts, evaluations, any models trained for you, and documentation
- How it is judged
- Hours returned, errors avoided, and revenue moved, against a baseline
- When it ends
- When your team can run it without us
A software vendor
- Who shows up
- An account team, then a support queue
- What you receive
- Licenses and a roadmap
- Where it runs
- In the vendor’s cloud
- Who owns it
- The vendor owns the platform
- How it is judged
- Seats activated
- When it ends
- When you stop paying
A strategy consultancy
- Who shows up
- Partners at the pitch, analysts after
- What you receive
- Recommendations
- Where it runs
- In a slide deck
- Who owns it
- You own the deck
- How it is judged
- Delivered on schedule
- When it ends
- When the report is accepted
IV / The engagement
Three stages, one handover.
One method for every engagement. Each stage ends at a decision you make, with what was promised in hand.
The Survey
Readiness assessment, Two to three weeks
We walk the floor before we write a line of code. We shadow your teams, map where hours go and decisions stall, audit data and systems, and rank every opportunity by value and feasibility.
You leave with
- A ranked register of opportunities, each with a business case
- A short list of what not to build, and why
- A data, systems, and risk review
- A ninety-day plan, with the first vintage chosen
You decide whether to continue. The Survey stands on its own.
The First Vintage
First production deployment, Six to ten weeks
A pod ships the first workflows into production inside your systems, built against evaluations drawn from your own cases and measured against the baseline set in the Survey.
You leave with
- Workflows running in production, in your stack
- Evaluation suites and live monitoring
- Runbooks and handover documentation
- Trained owners on your team
Go-live criteria are agreed before the build begins.
Tending
Evolution and expansion, Each season after
We measure, retrain, refine prompts and models, and extend to the next workflows, while your owners take on more of the work every season.
You leave with
- A quarterly vintage report: impact against the baseline, risks, and next bets
- Monitoring, evaluation on every change, and cost governance
- The next workflows, chosen with your owners
- An internal champions program
Every engagement is built to end. Success is how little you need us.
V / Where we work
Built for the companies others overlook.
We work with founder-led, family-owned, and investor-backed operators, and with enterprise teams. The work is organized by function, by industry, and by the workflows where AI tends to pay first.
By function
Marketing
Creative analysis, content operations, and experiments. Tests that conclude, and every claim checked.
Sales & revenue
Account research, CRM notes, proposals, and forecasts. More time selling, and a number you can defend.
Customer experience
Triage, agent assist, knowledge, and QA on every conversation, with a person always in reach.
Finance & FP&A
Forecasts, variance commentary, cash, and the board pack: sooner, with every number owned by finance.
Accounting & close
Reconciliations, journal review, and the month-end close: shorter, with the controls intact.
Operations & supply chain
Order exceptions, supplier follow-up, shipping paperwork, and S&OP: handled inside limits you write down.
People & talent
Interview logistics, HR questions, onboarding, and reviews, while people make every hiring and pay decision.
Legal & compliance
Contract review, obligations, privacy requests, and audit evidence: faster, with counsel deciding.
By industry
Healthcare & life sciences
Prior auth, referrals, revenue cycle, and regulated documents: prepared by AI, decided by people.
Financial services
KYC, AML, underwriting, claims, and advisor work: shorter queues, documented for your examiners.
Industrial & manufacturing
Maintenance, quality records, quotes, and field service, with no write access to control systems.
Food, beverage & agriculture
Allocation, traceability, labels, depletions, and trade spend, for growers, wineries, and food brands.
Consumer & retail
Product content, customer service, planning, and marketplaces, with every claim traceable to its source.
Real estate & construction
Leases, underwriting, investor reports, and project paperwork, drafted faster and decided by your people.
Professional services
Precedent search, proposals, conflicts intake, and billing, with client confidences intact.
Mission-driven & nonprofit
Grants, stewardship, program data, and compliance, with hours returned to the mission, at rates it can bear.
Growth-stage companies
Including our own portfolio: one pod, a few high-leverage workflows, and habits that scale with the company.
Mid-market operators
Where a handful of systems run most of the business and a handful of workflows hold most of the hours.
Enterprise teams
A function or business unit at a time, through your security review, procurement, and change management.
Mission-driven organizations
Reserved capacity each season, the same pod and rigor, at rates a mission budget can bear.
Investors and boards
AI diligence on a target before you buy, and a hundred-day value-creation plan for the companies you hold.
VI / Guardrails
Guardrails before growth.
Every agent has a job description, a supervisor, and an off switch.
Your data stays yours
We deploy in your cloud or tenant, under your identity and access controls. Your data trains only models you own, inside your tenant; it never trains ours, a model provider’s, or any model shared with another client.
Evaluated before it ships
Every workflow is tested against cases drawn from your own history, with accuracy thresholds agreed in advance and monitored after launch.
People where judgment lives
Human review is designed in wherever a decision carries clinical, financial, legal, or reputational weight, with escalation paths and audit trails.
Built to your regime
We design to the controls you already answer to, such as SOX, HIPAA, GLBA, and GDPR, and document against the NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
Model-agnostic
We choose models and tools on merit for each workflow and take no reseller margins, so you are never locked into our preferences.
Costs in plain sight
Inference and infrastructure costs are tracked per workflow from the first week, so the economics are as visible as the outcomes.
VII / Beyond the engagement
What a venture house can add.
Estate Grown is also a venture firm. That changes what an AI engagement can become: for you, and occasionally for an entire industry.
When a tool outgrows its owner
Sometimes what we build for you could serve a whole industry. When it can, our venture practice can help you spin it out, with you as a founding partner rather than a customer.
Distribution, introduced
Our strategic distribution practice brings you into rooms with partners, platforms, and customers you could not yet reach on your own.
Capital, when it fits
For companies we work alongside, patient capital is an option on the table. It is never a condition of the work.
Mission-driven work
A share of every season, held for the mission-driven.
Serious AI work should not be reserved for the largest budgets. We hold a standing share of our capacity for nonprofits and mission-driven companies, at reduced or at-cost rates, with the same pod, the same rigor, and the same handover.
Apply the usual way and tell us about the mission. We allocate reserved capacity each season by need, readiness, and fit, and help teams make use of the nonprofit programs the major AI providers offer.
Mission-driven & nonprofitThe Field School
Capability that stays after we leave.
Adoption is a skill, not a purchase. The Field School teaches leaders and teams to use AI well in their own work, and to run what we build together.
Explore the Field SchoolExecutive briefing
Half a day
Leadership working session
One day
Function workshops
Ninety minutes each
Champions program
Six weeks
Residency
Eight to twelve weeks
Office hours
Weekly
Policy and governance kit
Tailored to you
VIII / Questions
What buyers ask us first.
Who is this for?
Operating companies with real workflows and real data, from growth-stage to enterprise, and mission-driven organizations through our reserved capacity. If AI could return hours to one of your teams, we should talk.
How is this different from a consultancy or a software vendor?
A consultancy recommends; a vendor licenses. We embed engineers who build working systems inside your stack, measure them against a baseline, and hand them over. You own the result.
What does the Survey involve, and what do we receive?
Two to three weeks, at a fixed fee agreed up front. You receive a ranked register of opportunities with business cases, a data and systems readiness review, a risk assessment, and a ninety-day plan. All of it is useful whether or not you continue with us.
How is the work priced?
The Survey is a fixed fee, agreed before it starts. After that, work is priced by the season (one quarter), with the scope written down before each begins. Where impact can be measured cleanly against the baseline, we are open to tying part of our fee to it.
How soon will something be in production?
A first vintage is scoped to reach production six to ten weeks after the Survey, depending on data access and your security review. We agree go-live criteria before we build.
Which models and vendors do you use?
Whichever suits the workflow. We work across the major model providers, including Anthropic, OpenAI, and Google, and with open-weight models where data or cost demands it. We take no reseller margins.
Where does our data go?
Nowhere it should not. We deploy inside your cloud or tenant under your access controls, prefer read-only access, and sign the agreements your regime requires (a BAA, for instance). Your data trains only models you own, inside your tenant; it never trains ours, a model provider’s, or any model shared with another client.
Who owns what you build?
You do: the code, prompts, evaluations, any models trained for you, and documentation. There is no platform fee and nothing to unwind if we part ways.
Will this replace our people?
We build for capacity, not headcount. The aim is the same team taking on more, and spending its time on the judgment only it can provide.
What if a workflow does not work?
Then the evaluations will say so early. We set thresholds before launch and stop, adjust, or redirect a workflow that misses them before it reaches your customers.
Do you invest in the companies you work with?
Sometimes, and never as a condition. Estate Grown is also a venture firm; where an engagement reveals a company worth building or backing, we will say so plainly.
Begin with the Survey.
Two to three weeks inside your operation, a fixed fee agreed up front, and a plan you keep whether or not we build it together.