Forward deployed engineering for the AI use case that is defined, funded and still not live
AI Implementation Services
Most AI use cases do not fail at the idea stage. They fail in the gap between a convincing prototype and a feature that survives real users, real data and a release process. This practice closes that gap with a named engineer embedded in your stack, owning the use case until it is live. The finish line is production, not a recommendation, a deck or a pilot.
How a use case gets from prototype to live
A named engineer, your repository, an agreed definition of live and the review that closes the engagement.
90 secSample frame · video pending01Before any engineer is embedded
Three checks before an engineer is embedded
Embedding an engineer to take a use case live is a commitment on both sides. Three questions decide whether implementation is the right next step or a step taken too early.
Is the use case actually defined?
A defined use case has a named owner, a workflow it changes and a definition of live everyone will sign. Without those three, scoping comes first.
Who on your side can say yes?
The engineer will need access, data and decisions in week one. A technical owner with the authority to grant them is a precondition, not a courtesy.
What does live mean for this feature?
Accuracy, latency, cost per request and the fallback when the model is wrong all need agreed thresholds before the build starts, or nobody knows when it has finished.
| Practice | The question it answers | What you receive |
|---|---|---|
| AI consulting | Which use case deserves the investment? | A ranked shortlist and a costed recommendation |
| AI integration | How does a proven model reach our systems? | A data contract, a fallback and a live connection |
| AI implementation | How does this defined use case get to production? | The use case live, owned by a named embedded engineer |
| AI transformation | How does the whole organisation change? | A roadmap and a programme across many cases |
| Managed AI services | Who runs it once it is live? | Monitoring, drift control and cost management over time |
02Agreed before an engineer logs in
The ledger that keeps implementation honest
Every implementation engagement fixes the split before the first commit: what you bring, what the embedded engineer ships, what you receive at live, and what stays yours throughout.
- Your side
You bring
- The prototype and whoever built it
- The production environment it must live in
- The definition of live your technical owner will sign
- Our side
We ship
- The prototype rebuilt against production data and traffic
- Evaluation, guardrails and fallbacks the demo never had
- The release path through your own pipeline and reviews
- Your side
You receive
- The use case running for real users
- An evaluation suite that says whether it still works
- Runbooks written for the team inheriting it
Never leaves you
- The model provider and every account with it
- Product decisions about what the feature does
- The repository, the data and the deployment keys
Where the line sitsWe carry the use case over the line into production. What it is allowed to do stays your call.
03Forward deployed: from defined use case to live
How a forward deployed engagement runs
The engagement runs inside your repository and cadence rather than beside them. Each stage closes on something your technical owner can inspect and sign.
Fix the use case and the finish line
The engineer and your technical owner write down the workflow, the quality bar, the cost ceiling and the fallback. That document is what the engagement is measured against.
A definition of live your owner signsEmbed and ship the first increment
Access, data and tooling arrive in week one. The engineer merges a bounded improvement through your own pipeline, so the working pattern is proven early.
A first merge inside your review processEvaluate, harden and release
An evaluation suite runs against your real data. Guardrails, fallbacks and cost controls are added until the feature meets the agreed definition of live.
Evidence the feature holds under real trafficGo live and review
The feature ships with runbooks and monitoring your team owns. The practice lead reviews the outcome with you, and the engagement graduates or ends by its terms.
A structured review, then a chosen next step
04Three drivers, not a rate card
What actually drives implementation cost
Implementation is billed monthly per engineer on the mode's own band, so cost is a question of duration and composition rather than a fixed price. Three factors move both.
Distance between the current state and live
A prototype with a clear evaluation gap is a short road. A use case that still lacks data access or a workflow owner is a longer one.
One engineer or a pair
Most use cases need one engineer. A case spanning two disciplines, such as retrieval and a product interface, is staffed as a pair.
How fast access arrives
Week-one access to environment, data and tooling lets the first month go to shipping. Where access takes longer, the work takes longer by the same amount.
05Read this first
When implementation is the wrong starting point
Embedding an engineer against a use case nobody has defined would burn the first month on scoping at implementation rates. The alternative starting points are named before any pitch.
- Project Scoping
The use case is not defined yet
Project Scoping fixes the owner, the workflow and the definition of live first. Implementation starts only once those exist.
- AI Consulting
Several candidate cases compete for one budget
Ranking and feasibility testing belong to AI consulting, which decides what deserves the investment before anyone is embedded.
- AI Integration Services
The model is proven and only needs connecting
Wiring an existing model into your CRM, ERP or internal tools with a contract and a fallback is integration work.
| Shape | Best when | You direct | We carry |
|---|---|---|---|
| Forward Deployed Engineering | One defined use case must reach production | Access, data and decisions | The deployment plan and the use case to live |
| Team extension | The use case is live and you want the engineer under your direction | Priorities and reviews | Named engineers and continuity |
| Delivery pod | Further use cases or a programme are scoped after go-live | Product decisions each cycle | Engineering, testing, releases |
06Straight answers
Asked before an engineer is embedded.
01Is this forward deployed engineering?
Yes. The delivery model is a forward deployed engineer: one named engineer embedded in your stack who owns a defined use case until it is live, with a practice lead governing the work. The hire page describes the engagement terms; this page describes what that engineer ships.
02How is implementation different from AI integration?
Integration wires a model that already works into the systems your team uses, with a data contract and a fallback. Implementation owns a whole use case from its current state to live, including the evaluation, the guardrails and the release. Integration is often one task inside an implementation.
03Do you build on a particular model provider?
No. The engineer deploys whichever provider or self-hosted model fits your constraints, and the provider relationship stays with you. Where a switch is needed later, the boundary left behind makes it your team's change to make.
04Who manages the engineer during the engagement?
The engineer drives the deployment plan and the work on the use case. Your technical owner supplies access, data and decisions. A ValueCoders practice lead governs delivery through a weekly engineer check-in, a monthly call with you and a structured review at the end of the minimum term.
05Where does the engineer work?
Remote-embedded, in your repository, tools and cadence. The engineer drives the deployment plan and the work on the use case, and your technical owner supplies access, data and decisions.
06What has to be in place before you start?
A named technical owner, a defined use case with an agreed definition of live, and week-one access to environment, data and tooling. If the use case is not yet defined, the first offer is Project Scoping rather than an embedded engineer.
07How does an implementation engagement end?
By notice from either side, or at the structured review once the use case is live. Many clients then keep the engineer under their own direction through Team Extension, or scope further cases as a Delivery Pod.
08How is implementation priced?
Monthly, per engineer, on this mode's own band in the rate card, with a minimum term. The figure is stated in the proposal once scope and composition are agreed; no rate is published on the site.