Your AI team,
embedded in your business.
Product leaders and engineers embedded in your operations, accountable from discovery to measurable impact.
Not staff augmentation. Not consulting that ends at a slide deck.
Own the right problem. Build the right solution.
One deployment pod
Two capabilities. One accountable team.
Two disciplines. One accountable team.
- Business discovery
- Workflow + product strategy
- Priorities + success criteria
- AI architecture
- Agents + systems integration
- Deployment + reliability
One embedded pod, from workflow decisions to production.
Measure: time to production and rework effortThe two roles
Who does what.
FD Product
Own the right problem and business outcome.
Forward-Deployed Product Lead
Turn business problems into deployable AI products with accountable outcomes.
Responsibilities
- Discover real pain points with business and frontline teams.
- Map processes, decision rights, and baseline metrics.
- Prioritize by value, feasibility, adoption, and risk.
- Drive adoption and realized business value.
Typical artifacts
FDE
Build and operate the right technical solution.
Forward-Deployed Engineer
Turn a validated problem into a secure, reliable production AI system.
Responsibilities
- Assess systems, data, permissions, and integrations.
- Choose the right approach: models, agents, or plain software.
- Build on Amplent Platform or third-party technology.
- Deploy with evaluation, security, and observability.
Typical artifacts
Shared accountability
Who leads, who supports, what is shared.
Scope and success criteria distinguish what Amplent controls from outcomes that depend on client inputs, decisions, data availability, and adoption. Accountability is measurable without promising outcomes beyond the team's control.
| FD Product | FDE | Shared responsibility | |
|---|---|---|---|
| Problem definition | Leads | Supports | Agree on feasible framing |
| Business KPI selection | Leads | Supports | Measure actual impact |
| Product scope and UX | Leads | Supports | Validate user experience |
| Technical design | Consulted | Leads | Align to business constraints |
| Integrations and deployment | Consulted | Leads | Meet acceptance criteria |
| Governance and human approvals | Co-leads with client risk owners | Implements controls | Safe, accountable operation |
| Adoption and change | Leads | Supports | Achieve usable deployment |
| Reliability and operations | Monitors impact | Leads | Respond to production outcomes |
Engagement lifecycle
A named lead at every stage.
- 01
Discover
Interviews, observation, baseline metrics.
FD Product-led - 02
Design
Target workflow, approach, and acceptance criteria.
Product + FDE - 03
Build
Iterative delivery and integration.
FDE-led - 04
Validate
Acceptance, evaluations, and security checks.
Joint - 05
Deploy
Rollout with monitoring and rollback paths.
FDE-led - 06
Operate & expand
Track value and expand to adjacent workflows.
Joint / managed ops
Worked example
Leasing, faster, with controls intact.
A real-estate organization wants to accelerate leasing.
Success is measured in turnaround time, accuracy, and adoption, not the number of agents built.
- Baseline turnaround captured before any build
- Approvals designed with the finance owner
- Adoption tracked week by week
Ways to engage
One pod, shaped to the work.
The default is a forward-deployed pod with product and engineering together. Where the work calls for it, product leadership or engineering can be embedded on their own, and several pods can run as one program.
| Who is embedded | Best suited to | Typical starting point | |
|---|---|---|---|
| Forward-deployed pod | Product lead + engineer + fractional specialists | A full cycle from discovery to live, measured operation | One high-value workflow with a named business owner |
| Product leadership | Embedded AI product lead | Discovery, portfolio prioritization, and AI product direction | An opportunity map and a prioritized backlog |
| Engineering | Embedded engineer or engineering pod | Integration-heavy builds with product direction already set | An agreed architecture and acceptance criteria |
| Transformation program | Several pods with governance and training leadership | Multi-workflow, multi-department change | A roadmap sequenced by value and readiness |
Our promises
What makes the model different.
Outcome ownership
Accountable for KPIs, not tasks.
No lock-in
Amplent components where they fit, never forced.
Production responsibility
Built with evaluation and security in view.
Human accountability
Critical decisions stay with people.
Built with embedded teams.
EventsTurn event recommendations into the right meetings.
Read the story
Sales technologyTurn relationship data into opportunities.
Read the story
Technology servicesBecome AI-native, from lead to handover.
Read the story
RetailRun marketing and customer responses automatically.
Read the story
Real estateGo from land to feasibility study and live project control.
Read the storyPredict missed appointments and keep patients on schedule.
Read the storyYour AI team,
embedded in your business.
Tell us the workflow and outcome, and we will propose the pod.
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