Use-case library
Sales · Claude.ai
Prepare for sales deals
Research prospects and organize your talking points before an important meeting.
Retrieval-grounded assistantAutonomy: SuggestRevenueSpeedLow effortPartner / MD
What changed
Claude builds a pre-meeting brief — the account's priorities, likely pains, stakeholders, and tailored talking points — so reps walk in prepared instead of improvising.
How it's built
Retrieval-grounded assistant (rung 3 of 6). Fetch your evidence, then answer. Fixed path, read-only.
Not an agent: the sequence of steps is fixed in advance, so the whole path can be tested end to end.
- Autonomy: T0 · Suggest
- Surfaces information, ranks, or recommends. Changes nothing. Human role: does all the work; may ignore the system entirely.
- How it is governed
- Cite-or-abstain. Source freshness and access controls inherited from the corpus.
What the certification exams call this
- Anthropic (Claude Certified Architect – Foundations (CCAR-F))The augmented LLM: a model with retrieval. source
- OpenAI (OpenAI agent guidance (Agents SDK, Codex, OpenAI Academy))Data tools that retrieve the context the answer needs. source
- Google Cloud (Generative AI Leader)Grounding in first-party enterprise data; retrieval-augmented generation (exam §3.3). source
- Microsoft (AI-901 (Azure AI Fundamentals) and AB-100 (Agentic AI Business Solutions Architect))Knowledge sources and grounding data for Copilot Studio agents (AB-100). source
How Koko classifies AI · the full ladder is taught in AI & Agentic Delivery Foundations.
Try it
Illustrative demoA rep has a first call with a CFO tomorrow and 20 minutes to prep. Edit the inputs to tailor the output — it's baked synthetic data, so nothing leaves your browser until you run it live.
Example prompts
- Build a pre-call brief for [prospect]: priorities, likely pains, who's in the room, and 5 tailored talking points.
- Draft 4 discovery questions that map our strengths to their stated initiatives.