Choose
Define the provider type that best fits the business problem.
Resources for understanding budgets, evidence, risks and the questions to ask before choosing an AI service provider.
Define the provider type that best fits the business problem.
Use one consistent framework to read several offers.
Plan for setup, tools, maintenance and internal time.
Connect each piece of evidence to the relevant use case.
Clarify scope, owners, data and success criteria.
Choose the right role based on the decision, delivery needs and expected integration level.
Structure the need, data, constraints, deliverables and success criteria.
Choose the engagement format to buy and the decision expected at the end of each stage.
Compare business need, scope, evidence, data, integrations, security, budget, acceptance criteria, maintenance and reversibility using one consistent framework.
Case studies, demos, deliverables, references and private evidence: distinguish a commercial promise from evidence that is useful for a buying decision.
Break down scoping, data, POCs, integrations, deployment, training, tools, maintenance and internal time, with public AIPartnerLens amounts where available.
Assess scoping, evidence, data, proposals, production, maintenance and reversibility.
Separate scoping, POC, development, integrations, tools, maintenance and internal time.
Understand how to compare AI service providers by use case, budget, evidence, risks, tools and fit.
Read the comparison pageIdentify suitable profiles for automation, customer support, training, internal documents or AI strategy projects.
Compare profilesA clear need, an initial scope and a few expected pieces of evidence make proposals easier to compare consistently.
Write down the business problem, users involved, existing tools, indicative budget and the evidence you want to review.
Guides complement the comparison. They do not replace legal, security or technical scoping when a project requires it.