From Pilots to Platforms: Consolidating AI Foundations

Cross-Industry • ~7–8 min read • Updated Apr 15, 2025

Context

Organizations that scaled dozens of AI pilots now face duplicate tooling, fragmented data flows, and inconsistent guardrails. A platform-first approach consolidates foundations, accelerates delivery, and lets business teams build on reliable “golden paths” instead of reinventing the stack in every line of business.

Core Framework

Move to a platform model built on four layers and clear product ownership:

  1. Unified Data & Features: Centralized data contracts, governed access, and a shared feature store to curb one-off pipelines.
  2. Model & Inference Services: Standardized model registry, deployment, observability, evaluation, and rollback; prompt/agent management for GenAI.
  3. Workflow & Reuse: Reusable components (ETL, vectorization, retrieval, evaluation), orchestration, and CI/CD templates (“golden paths”).
  4. Platform Enablement: Identity and access management, FinOps and cost guardrails, security controls, and developer experience (docs, SDKs, templates).

Recommended Actions

  1. Inventory & Rationalize: Catalog pilots, tools, vendors, and spend; identify redundancies and shadow platforms to retire within 60–90 days.
  2. Define the Platform Charter: Appoint a platform product owner; set SLOs (availability, latency, cost), intake rules, and a public roadmap.
  3. Stand Up Shared Services: Launch core services (feature store, registry, inference gateway, prompt store) with APIs and usage quotas.
  4. Establish Golden Paths: Provide pre-approved templates for common patterns (RAG, classification, forecasting, agents) and automate scaffolding.
  5. Fund Centrally, Meter Locally: Centrally fund the core platform; use consumption-based chargeback by team or product to drive efficient usage.
  6. Migrate & Decommission: Sequence migrations by value and risk; define cutover criteria and success metrics, then deprecate duplicative stacks.

Common Pitfalls

  • Over-centralization: A platform that slows teams with heavy gates and bespoke approvals.
  • No Product Discipline: Treating the platform as a project, not a product with owners, SLOs, and a roadmap.
  • Underpowered Observability: Lack of telemetry for data drift, cost spikes, and safety events.
  • Unclear Funding Model: Cost surprises without FinOps and transparent metering.

Quick Win Checklist

  • Publish a one-page platform charter with owner, SLOs, and intake rules.
  • Ship “hello world” golden paths for 2–3 common patterns with CLI/SDK templates.
  • Create an internal platform status page and API catalog.
  • Turn on basic FinOps: budget caps, alerts, and monthly chargeback reports.

Closing

Consolidating pilots into a shared AI platform yields faster delivery, safer operations, and better capital efficiency. Treat the platform as a product, measure it with SLOs, and give teams paved roads — not roadblocks.

Advisory by Straten AI Team

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