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The right AI data platform is the one that fits your defined workloads, data boundaries, governance model, security responsibilities, operating capacity, and cost drivers—not the one with the longest feature list. Start by documenting who will use the platform, which source systems and sensitive data it will touch, what model or agent actions are permitted, and what failure would cost the business. Then make each vendor prove the same workload, policies, audit evidence, deployment boundaries, and billable-unit assumptions. No universal winner or reliable cross-vendor price comparison is established here; the defensible purchase is a configuration-specific decision backed by demonstrations, responsibility mapping, and a workload quote.
What should you define before evaluating an AI data platform?
Define the workload and its boundaries before reading feature pages. A platform that is excellent for governed analytics may be a poor fit for retrieval, model serving, or agent actions if its identity, network, or policy model cannot follow those requests.
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- Users and callers: list employees, applications, partners, automated jobs, and service identities. Include expected concurrency and whether callers are internal or external.
- Source systems: identify warehouses, lakes, SaaS applications, files, operational databases, APIs, and event streams. Record ownership, refresh frequency, and existing access controls.
- Information handled: classify personal, financial, health, confidential, regulated, and public data. State whether prompts, retrieved records, model inputs, outputs, and tool results may contain each class.
- Actions: separate read-only analytics and retrieval from write actions such as creating tickets, changing records, sending messages, or initiating transactions.
- Business impact: document latency, availability, accuracy, explainability, retention, and recovery targets. Describe the consequence of a wrong answer, unauthorized disclosure, or unsafe action.
- Geography and deployment: specify regions, residency requirements, cloud accounts, network zones, on-premises systems, and whether a connected system must remain outside the platform.
Microsoft’s Cloud Adoption Framework treats readiness, architecture, governance and security baselines, and operational standards as connected platform work. Use that sequence as a planning check: an architecture that cannot meet your identity or operating requirements is not rescued by an attractive model catalog.
Turn boundaries into acceptance tests
For every in-scope workload, write a test that a vendor must run with representative data and permissions. Examples include a contractor seeing only approved records, a revoked service identity being denied immediately, a request exceeding its budget being blocked, and an administrator producing an audit record that identifies caller, asset, policy decision, and outcome. Acceptance tests prevent a polished demo from hiding integration or control gaps.
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What is the difference between an API platform, API management, an API gateway, and governance?
They are related but not interchangeable. Ask a supplier to name the component that performs each function and identify what remains your responsibility.
| Term | What it normally covers | Questions to ask |
|---|---|---|
| API platform | A broader set of design, publication, lifecycle, security, analytics, and runtime capabilities, sometimes including AI-service management. | Which components are included, and which require separate products or subscriptions? |
| API management | Lifecycle operations such as design-time controls, catalogs, developer access, versioning, policies, and usage analysis. | Who owns API definitions, approvals, versions, deprecation, and consumer onboarding? |
| API gateway | A runtime enforcement point for selected traffic policies, routing, authentication, authorization, transformations, and limits. | Which policies run on every path, and what happens when traffic bypasses the gateway? |
| Governance | Decision rights, standards, ownership, exceptions, lifecycle rules, control evidence, and review processes across people and technology. | Where are standards recorded, who can grant exceptions, and how is compliance demonstrated? |
WSO2’s API Platform Overview distinguishes a full platform from a gateway-only path. Apache APISIX’s governance guidance similarly separates governance and management from the gateway’s runtime enforcement. A gateway can enforce a rate limit; it cannot, by itself, decide who owns an API, approve an exception, or prove that a retired model was removed from every client.
Map every required function to an owner
Request a component diagram showing design time, runtime, identity, policy, catalog, logging, and billing paths. For each function, record whether it is supplied by the platform, your cloud provider, a connected system, or your team. This exposes “platform” proposals that quietly depend on another gateway, catalog, identity service, SIEM, secrets manager, or custom policy engine.
How do you compare workload and architecture fit?
Compare platforms against the same representative workload, not a generic checklist. The most useful evidence is a working architecture and demonstration using your sources, permissions, network constraints, and failure cases.
| Comparison axis | Buyer questions | Evidence to request |
|---|---|---|
| Workload fit | Does it support analytics, retrieval, model use, agent actions, or a combination? Are required data types and users supported? | Workload-specific architecture and demonstration with representative sources and permissions. |
| Architecture and deployment | Where do data, prompts, outputs, logs, and policy decisions run? Can required regions and network zones be retained? | Data-flow, trust-boundary, isolation, connectivity, and disaster-recovery diagrams. |
| Integration | Can it connect to each source and preserve source-system permissions, freshness, lineage, and deletion behavior? | Connector behavior, synchronization schedule, error handling, and permission-mapping demonstration. |
| Performance and resilience | What latency, throughput, concurrency, and recovery behavior is supported for your workload? | Workload test plan, service limits, scaling method, and recovery procedures. Do not accept unrelated benchmarks. |
| Lifecycle | How are models, prompts, tools, connections, APIs, and policies versioned, approved, rolled back, and retired? | Promotion workflow, approval records, rollback demonstration, and decommissioning procedure. |
Test the uncomfortable paths
- Use a source record that a permitted user can see and another that the same user cannot.
- Revoke a role or token and measure when access actually stops.
- Send malformed, oversized, repeated, and over-budget requests.
- Disable a dependency and observe retries, fallback, queueing, and user-facing errors.
- Delete or correct source data and verify propagation to indexes, caches, embeddings, logs, and derived assets.
- Ask for an export of the evidence needed for an audit without vendor-side manual intervention.
How should AI asset and traffic governance be evaluated?
Evaluate both what the platform manages and what callers are allowed to do. Governing a model or connection without governing requests can leave cost, abuse, and data-exposure paths open; governing traffic without an inventory of assets makes policy scope unclear.
Asset governance questions
Ask how the platform represents and controls models, tools, connections, datasets, prompts, agents, indexes, and other reusable resources. Determine whether each asset has an owner, classification, approved environment, version, lineage, and retirement state. Verify inheritance and delegation: can a project team use an approved connection without obtaining broader access to its credentials or underlying data?
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Databricks documents one approach in which Unity Catalog is used for asset governance. Treat that as a vendor-specific example and verify the exact edition, region, and deployment rather than assuming equivalent controls elsewhere.
Traffic governance questions
Ask where caller identity is established and preserved, where authorization is evaluated, and whether policies apply to synchronous calls, asynchronous jobs, batch runs, and tool invocations. Request demonstrations of route selection, rate limits, budgets, quotas, content or data policies, and usage records. Confirm whether a request that fans out to several models or tools produces one traceable cost and policy record or several disconnected records.
Databricks describes traffic governance through Unity Gateway, including request routing, rate or budget controls, and usage tracking. Confirm which controls are available for your workload and how they interact with external gateways, model providers, and source-system authorization.
Evidence that governance worked
A policy page is not evidence of enforcement. Require a log or report showing the caller, asset, request route, policy evaluated, decision, timestamp, usage, and any downstream action. Ask how records are retained, protected from alteration, exported, and correlated with your incident and financial systems.
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Security is a shared-responsibility design exercise. The platform’s controls matter, but your team still owns decisions about identities, data classification, configuration, connected systems, and operational response.
Build a responsibility map
| Control area | Questions for the supplier | Buyer confirmation |
|---|---|---|
| Identity and access | Which identity providers, federation methods, service identities, roles, and conditional controls are supported? | Every human and machine caller has a least-privilege role, lifecycle owner, and revocation process. |
| Data protection | Where are data, prompts, outputs, embeddings, caches, backups, and logs stored? Which encryption keys and deletion controls are available? | Classification, retention, residency, key ownership, and deletion requirements are mapped to each data flow. |
| Network boundaries | Can traffic use private connectivity, approved egress, segmentation, and inspection? Which endpoints are mandatory? | Routes, firewall rules, DNS, certificates, and egress monitoring are operated and tested. |
| Policy enforcement | Which controls run before a request, during routing, after a response, and on tool actions? | Policies are versioned, tested, approved, monitored, and covered by incident procedures. |
| Monitoring and response | What telemetry, alerting, support escalation, and forensic export are included? | Operations can detect misuse, contain a compromised identity, preserve evidence, and notify affected owners. |
| Assurance | Which certifications, attestations, penetration-test summaries, and contractual commitments apply to the exact service and region? | Procurement and legal teams verify scope, dates, exclusions, and subprocessor terms. |
Microsoft’s cloud guidance places governance and security baselines alongside architecture and operational standards. Microsoft Azure API Management documentation describes runtime controls such as authentication, authorization, and rate limiting; verify where those controls sit in your proposed topology and what happens to traffic that does not traverse the service.
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Ask about data use, not only data storage
Clarify whether prompts, retrieved content, outputs, telemetry, and support artifacts are used to train or improve services; how long they remain; and who can access them. Require the answer in contractual language for the selected edition and region. A statement about encrypted storage does not answer whether data is copied into logs, caches, backups, or provider-operated troubleshooting systems.
Who should operate the platform after purchase?
Define operating ownership before signing. A platform without a workable operating model becomes an unmanaged collection of connectors, exceptions, and untracked spend.
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Assign decision rights
- Platform team: baseline architecture, shared environments, connectivity, upgrades, reliability, and common controls.
- Data and AI owners: asset classification, approved use, quality thresholds, model or tool lifecycle, and business risk acceptance.
- Security and privacy: identity standards, threat modeling, monitoring requirements, incident response, and regulatory interpretation.
- API owners: contracts, schemas, versions, consumer access, deprecation, and runtime objectives.
- Finance: budgets, allocation, forecasts, chargeback or showback, and review of abnormal usage.
- Connected-system owners: source permissions, data quality, availability, deletion, and transaction safeguards.
Document a RACI or equivalent responsibility map for standards, exceptions, approvals, monitoring, evidence, and retirement. Include a support model with severity definitions, escalation contacts, maintenance windows, and the time zone in which assistance is provided.
Make exceptions visible
Governance should provide a time-limited exception process rather than informal bypasses. Each exception should name the owner, affected assets and traffic, compensating controls, expiry date, approval authority, and evidence that the risk was reviewed. Ask vendors how those records integrate with your existing workflow; if the platform cannot represent them, plan an external register.
What pricing questions should you ask?
Ask what is billed, how it is counted, what is included, and how the bill changes as workloads, assets, environments, and traffic grow. Do not compare a platform fee with a gateway fee or model-token estimate as though they were the same unit.
Record the billable units
- Governed assets and the definition of an asset.
- Requests, calls, transactions, tokens, model invocations, or tool actions.
- Compute, storage, data transfer, indexing, orchestration, and environment charges.
- Minimum commitments, reserved capacity, included quotas, and overage behavior.
- Development, test, disaster-recovery, and multi-region environment treatment.
- Support tier, implementation services, training, and premium connectors.
- Renewal rules, price-change notice, currency, taxes, and termination or export costs.
Understand the counting interval and attachment rules
Microsoft Purview’s Data Governance Billing FAQ says its new data-governance pricing model took effect January 6, 2025. The FAQ describes daily counting of unique governed assets and examples in which attached assets are counted. This is a product-specific billing example, not an industry-wide rate or a current quote for another platform. Ask each supplier for the equivalent counting definition, including whether inactive, duplicated, linked, or automatically discovered assets incur charges.
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Model a realistic workload
Give every bidder the same assumptions: asset inventory and growth, daily and peak requests, average and maximum payload, model and tool mix, retention, environments, regions, support level, and expected five-year change. Request a line-item quote and a month-by-month usage model for low, expected, and high cases. Separate recurring subscription, variable consumption, implementation, migration, and exit costs so a low entry price cannot conceal expensive growth.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do you run a fair proof of concept and procurement?
Use a staged process that produces comparable evidence and a decision record.
- Freeze scope: approve the workload statement, data classifications, regions, users, actions, success measures, and prohibited uses.
- Issue the same evidence request: send each supplier identical architecture, governance, security, operations, support, and pricing questions.
- Shortlist by hard gates: remove options that cannot meet residency, identity, network, action-safety, or contractual requirements before scoring features.
- Run a controlled demonstration: use representative sources, permissions, failure cases, and traffic limits. Record configuration, edition, region, and date.
- Inspect evidence: collect logs, policy outcomes, lineage, usage records, audit exports, recovery results, and administrative steps. Screenshots alone are insufficient.
- Validate operations: rehearse onboarding, role change, incident escalation, upgrade, rollback, backup, restore, and asset retirement.
- Price the same scenario: provide common assumptions and require a line-item quote, counting rules, included features, support, and overage terms.
- Score and document: record pass, fail, partial, dependency, owner, remediation, and contract condition for every requirement.
- Contract the proof: convert critical demonstrations and limits into service descriptions, security terms, data-use restrictions, support obligations, and termination assistance.
Use a weighted decision score
Weight criteria according to business risk rather than vendor marketing. A regulated write-action workload may give security, identity, auditability, and recovery more weight than model breadth. A research retrieval workload may emphasize source freshness, permission propagation, lineage, and variable-cost controls. Keep mandatory gates separate from weighted preferences: a low score cannot compensate for a failed legal or residency requirement.
What are the most common buying mistakes?
Choosing a catalog instead of a control plane
A large model or connector catalog does not prove that identities, requests, budgets, and actions are governed. Require an end-to-end trace from caller to source, model, tool, response, and bill.
Assuming a gateway equals governance
Runtime authentication and rate limiting are valuable, but governance also needs ownership, standards, approvals, lifecycle, exceptions, and evidence. Identify controls outside the gateway and fund the people and processes that operate them.
Accepting “secure by default” without topology
Ask where data and logs travel, which identities are used, what is public or private, and how non-platform traffic is controlled. A default setting is not a substitute for a workload-specific architecture review.
Comparing headline prices
Different vendors count different units and bundle different capabilities. Recalculate each proposal using common workload assumptions, including attached assets, environments, support, transfer, and growth.
Ignoring retirement and exit
Require export formats, deletion behavior, dependency inventory, credential rotation, and transition assistance before approval. An AI platform becomes a long-term dependency when its indexes, prompts, policies, and logs cannot be moved or proven deleted.
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What should a final recommendation contain?
Your recommendation should name the selected configuration and the evidence behind it, not merely a product. Include the approved workloads and exclusions, architecture and data boundaries, governance coverage for assets and traffic, security responsibility map, operating RACI, acceptance-test results, pricing assumptions, sensitivity cases, contractual conditions, and unresolved risks with owners and dates. If no option passes the hard gates, the correct decision is to narrow scope, change the architecture, or defer purchase rather than declare a winner.
Frequently Asked Questions
How many vendors should an enterprise shortlist?
Use enough candidates to test different architectural approaches, then eliminate any that fail mandatory identity, residency, integration, or contractual requirements. A smaller shortlist with identical evidence requests is more useful than a large feature comparison that cannot be validated.
Should API governance be centralized or owned by each team?
Set organization-wide minimum standards and decision rights, while allowing domain teams to own API contracts and workload-specific policies within those boundaries. Central teams should provide reusable controls and evidence; local teams should remain accountable for business data and behavior.
How can we estimate AI platform costs when usage is uncertain?
Model low, expected, and high scenarios using the vendor’s exact counting rules and include asset growth, attached resources, environments, support, and overages. Reconcile the model against a limited production-like pilot and require alerts or budget controls before expansion.
What evidence should security reviewers keep from a vendor evaluation?
Keep the versioned architecture, data-flow and trust-boundary diagrams, configuration exports, policy and audit-log samples, test results, responsibility map, contractual answers, and dated pricing assumptions. Store the evidence with the approval record so a later edition or region change can be reassessed.
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