AI Software RFP Template: What to Ask Before Hiring an Agency
A buyer-side checklist for evaluating AI software agencies, implementation partners, and product engineering teams.
A good AI software RFP does not ask vendors to promise magic. It asks them to explain architecture, data handling, evaluation, security, ownership, timeline, and maintenance. The goal is to separate production teams from demo builders.
Core RFP sections
- Business objective: what metric should improve?
- Workflow: what process exists today and who owns it?
- Data sources: where does the system read and write?
- AI requirements: generation, classification, extraction, search, agents, or forecasting.
- Evaluation: how will accuracy, safety, and usefulness be measured?
- Security: access control, logging, PII handling, retention, and vendor data use.
- Ownership: code, prompts, datasets, infrastructure, and documentation.
Questions every agency should answer
- What failure modes do you expect?
- How will you evaluate outputs before launch?
- Which parts are deterministic and which use AI?
- What happens when the model provider is down?
- How do we reduce cost as usage grows?
Red flags
Be careful when a vendor cannot explain evals, ignores data privacy, recommends agents for every workflow, or gives a fixed timeline without seeing integrations. AI projects fail because the unknowns are hidden, not because the model is weak.
FAQ
Frequently asked questions
What should an AI RFP include?+
It should include business goals, workflows, data sources, integration requirements, security rules, evaluation criteria, ownership terms, and maintenance expectations.
How do you compare AI agency proposals?+
Compare clarity of architecture, risk handling, evaluation plan, relevant experience, and maintenance approach — not just price.
Building something similar?
Let's talk in 30 minutes.