> For clean Markdown of any page, append `.md` to the page URL.
> For a complete documentation index, see https://docs.sarvam.ai/llms.txt.
> For full documentation content in one file, see https://docs.sarvam.ai/llms-full.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.sarvam.ai/_mcp/server.

# Lead follow-up

Qualify and follow up on leads, repeatably for every lead. An agent can research an inbound lead, score it against your rubric, draft a tailored follow-up, and update your records.

## What it uses

| Piece                                            | Role                                                                      |
| ------------------------------------------------ | ------------------------------------------------------------------------- |
| [Skills](/cowork/build/skills)                   | Your scoring rubric and follow-up format, applied the same way every time |
| [Connectors](/cowork/build/connectors)           | Your CRM and email, to update records and send follow-ups                 |
| [Knowledge Bases](/cowork/build/knowledge-bases) | Product and pricing material to ground the outreach                       |

## How to build it

1. Capture your scoring rubric and follow-up style as a **Skill**.
2. Add the connectors for your CRM and email.
3. Create an agent that researches the lead, scores it, drafts a follow-up, and updates the record.
4. Test it in the playground on a few real leads, then run it for every new lead.