Pods Overview
A Pod is a senior, cross functional team that embeds with you to deliver a production grade use case fast, with governance built in.
Small teams, big outcomes
What is a Pod
A Pod brings together product, data, engineering, and governance in one accountable team. It is designed to reduce handoffs, shorten feedback loops, and transfer capability to your people as value is delivered.
Why Pods work
Focus on one outcome at a time
Decisions made by the team that is building
Controls are implemented where work happens
Adoption is designed in from day one
When to use a Pod
You want measurable value in thirty to ninety days
You are moving from pilots to scale and need a credible path
Your use case touches multiple systems or teams
You need delivery and governance to move together
Pod Lead
Aligns outcomes, removes blockers, owns delivery
Product Partner
Frames the problem, defines value, manages scope
Data & Integration Engineer
Connects sources, pipelines, and retrieval
Pod size is typically five to seven, adjusted to context and risk.
AI Engineer
Prompts, orchestration, evaluation harness
Pod Roles
Experience Engineer
Workflow, UX, and adoption signals
Risk and Compliance Partner
Controls, approvals, and evidence
Enablement Coach
Training, quick references, and capability transfer
How Pods run
Orientation, one to two weeks
Align on the outcome, constraints, and success measures. Select a lighthouse use case with clear value and manageable risk.
1
2
Build, thirty to ninety days
Stand up data flows, retrieval, prompt and tool design, orchestration, and the evaluation harness for quality, cost, and latency. Release value to a defined audience with audit trail and access controls.
Scale, next ninety days
Harden and expand. Add observability and role-based access. Roll to the next group. Publish playbooks and training.
3
Transfer, ongoing
Enable your teams to own the solution. Establish a community of practice, dashboards, and light audits.
4
What you get
Working solution adopted by real users
Evaluation dashboard for quality, cost, and latency
Governance pack with risk tiering, approval paths, and audit trail
Reference architecture and playbooks
Enablement kit, quick references, and office hours
Where Pods deliver fast wins
Decision operations: reduce request to decision time with retrieval, scoring, and explanations
Knowledge operations: secure retrieval over policies and procedures, reduce time to resolve
Customer operations: guided responses and copilots that improve quality and consistency
Engineering operations: test generation, logs triage, and documentation acceleration
Back-office operations: finance, HR, and legal workflows with control evidence
Built in governance
Data lineage and sourcing documented
Role based access, least privilege, and logging
Human oversight for material decisions and edge cases
Bias screens and red team exercises
Policy inside the workflow so compliance is automatic
Metrics we sign up for
Lead time to value
Quality and control posture
Predictability of delivery
Adoption and sustained usage
Pod versus alternatives
Pod
Outcome based, single accountable team
Governance integrated
Capability transfer included
Staff augmentation
Extra hands, unclear ownership
Governance is separate
Limited transfer
Centralized COE only
Guidance from afar
Slow to ship
Adoption not guaranteed
Pricing and formats
Lighthouse Pod
Fixed scope, single use case, thirty to ninety days
Scale Pod
Additional use cases or new groups, adds observability and change operations
Advisory add on
Executive checkpoints, policy, and architecture reviews
Commercial terms can be aligned under MSA, SOW, and NDA.
FAQs
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Yes. Controls and evidence are built into the solution from day one. We collaborate with risk, audit, legal, and security.
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We set clear metrics in orientation and track them on the evaluation dashboard and adoption scorecards.
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You own the solution. We provide light audits and additional Pods as needed.