Answer the Buyer: A Sales Engineer Copilot
Build a retrieval copilot that answers technical buyer questions from product, security, and integration documents, with citations and honest gaps.
Why this matters
Sales engineers answer the same technical questions across security reviews, integration scoping, and product depth, and a wrong answer in a security questionnaire erodes trust or kills a deal. A copilot that answers from the real documents with citations speeds the cycle, but only if it refuses to guess when the documents do not cover the question.
Persona
Sales engineer at an enterprise SaaS company
Current manual workflow
The sales engineer searches scattered product docs, security policies, and integration guides, copies relevant passages into an answer, and checks each claim against the source before sending.
The AI workflow to build
The copilot retrieves passages from the product, security, and integration corpus, drafts an answer grounded in the retrieved text, and attaches a citation to every claim. When the corpus does not contain the answer, it says so and points to the nearest relevant material rather than inventing a response.
Inputs
- product documentation
- security and compliance docs
- integration guides
- a buyer question
Outputs
- a cited answer
- source links per claim
- an explicit not-covered response when applicable
Definition of done
On a synthetic question set that includes questions the corpus cannot answer, every answer carries a citation traceable to the source, unsupported questions return an explicit not-covered response, and no answer asserts a capability absent from the documents.
A buyer question: does the product support SCIM provisioning with Okta, and is data encrypted at rest?
Encryption at rest: yes, AES-256, cited to the security doc. SCIM with Okta: not covered in the current documents; the nearest reference is the SAML SSO guide. The copilot does not assert SCIM support.
Data plan
synthetic data
Boundaries and non-goals
- asserting unsupported capabilities
- real customer or security data
- CRM integration
Evaluation ideas
- citation accuracy
- groundedness
- not-covered recall on unanswerable questions
- answer correctness against a key
Run Level target
R2 Visible Plain translation: handles real cases.
Scope envelope
Buildable by one solo builder in 20 to 30 focused hours, on public, synthetic, or sanitized data, with a demo path that requires no production access.
Suggested tools
Suggested options, never requirements; briefs are tool-agnostic.