AI Stack Optimizer — Reduce Tool Sprawl

AI Stack Optimization Report — Initial Evidence Review

Executive summary

The supplied inventory, cost export, and team list can support a first-pass portfolio review. No specific product, owner, usage level, contract term, overlap, or savings figure is asserted here because the source rows have not been provided in this example. Treat all findings below as a structured review plan until evidence is mapped.

Evidence and inventory

Normalize each item by vendor, exact product, plan/tier, model or deployment, owner, business unit, and status. Link each row to its source and “as of” date. Reconcile inconsistent names before counting products. Keep missing owner, seat count, usage, annualized spend, contract end, and renewal-notice dates as unknown rather than filling estimates as facts.

Capability and job map

Map each verified product to the capability it provides and the business job it supports—for example, foundation model/API, copilot, agent platform, automation, knowledge/RAG, evaluation, or security. Record who uses the capability, for which workflow, and what outcome or service level is required. Similar product labels alone do not prove duplication.

Rationalization tests

For suspected overlap, compare actual users, jobs, quality, adoption, suite integration, controls, data boundaries, reliability, and switching costs. Classify each item as Keep, Optimize, Consolidate, Replace, Retire, or Investigate. Before any retirement, check downstream integrations, data exports, identity dependencies, business owners, and fallback requirements.

Economics and migration

Model scenarios only after reconciling spend, seats, usage, contracts, and exit costs. Show assumptions and ranges; do not promise savings. For a validated change, propose a limited pilot, success measures, parallel-run period if needed, checkpoint, rollback trigger, accountable owner, and renewal timing.

Next evidence needed

Provide row-level product and plan names, cost period/currency, seat and usage data, owners, business jobs, renewal/notice terms, integrations, data sensitivity, and known service requirements. The next pass can then quantify supported overlap and prioritize actions with confidence levels.