Product

Sidekick Recap

Meeting and call recordings in, structured summaries out — decisions, action items, follow-ups, sentiment — and writes back to your CRM, ticketing, or project tool through MCP rather than ending up as another note nobody opens.

Or build it custom →
Surfaces
Web · Mobile · Voice · Multi-channel
LLM
Provider-agnostic via gateway
Ownership
You own the infrastructure
Sidekick Recap — product meeting · 42 min
Decision: launch moved to the 15th — supplier risk
Action: Marie confirms stock levels by Thursday
Action: client brief to draft — assigned to Hugo
Written back to CRM and project tracker ✓
Illustrative interface — every deployment is styled to your brand and connected to your systems.

What you get

Drop a meeting recording (or a sales call, or a customer success conversation) in; get back a structured summary with decisions made, action items assigned, follow-ups scheduled, sentiment trajectory, and named participants. The summary writes back to your CRM, ticketing, or project tool through MCP — so the notes end up where the work happens, not in a separate notes app nobody reopens.

What makes it different

The market is crowded — Fireflies, Otter, Granola, Gong all take meetings in and produce summaries. The difference here is the connection back to your stack. Sales call → Salesforce or HubSpot update. CS call → Zendesk note with the action item assigned. Internal meeting → Linear or Asana ticket. We don't compete on transcription quality; we compete on making the summary actually useful by writing it where it matters.

What it can do for you

Sales calls become CRM updates without the rep typing. CS calls become tickets with the right follow-up scheduled. Internal decisions become action items in the project tool. Sentiment trends become a leadership dashboard. The output is structured, not just text.

  • Decisions, action items, follow-ups, sentiment per recording
  • Writes back to CRM, ticketing, project tools through MCP
  • Speaker identification across the conversation
  • Per-team templates for what to extract
  • Multi-language transcription and summary
  • PII redaction at capture
  • Searchable archive with stable identifiers
  • API + webhooks for custom integrations

Who it's for

Sales orgs with too many calls and not enough CRM hygiene. Customer success teams where notes end up scattered. Product orgs that want decision logs without manual upkeep. Anyone whose meeting volume is a real signal they're not capturing structurally.

How we ship it

Typical deployment is 2-3 weeks. We connect your meeting source (Zoom, Google Meet, Teams, recording uploads), connect your downstream tools through MCP, configure the per-team extraction templates, and pilot with a single team.

Questions people actually ask

How is this different from Otter, Fireflies, or Granola?

We don't compete on transcription quality — those tools are fine at it. The difference is where the summary goes: a sales call becomes a Salesforce or HubSpot update, a customer success call becomes a Zendesk note with the follow-up assigned, an internal meeting becomes a Linear or Asana ticket. The notes land where the work happens, not in a separate app nobody reopens.

What about sensitive things said in meetings?

PII (personal information like names, numbers, and account details) is redacted at capture where you configure it, and the searchable archive lives under your control with stable identifiers. Write-backs to your CRM or ticketing go through MCP connections you approve — the system writes only where you've said it can.

What do we need to connect, and how fast is it running?

Your meeting source — Zoom, Google Meet, Teams, or recording uploads — and the downstream tools you want summaries written to. A typical deployment is 2 to 3 weeks: connect the sources, configure per-team extraction templates (what each team wants pulled out), and pilot with a single team.

If we build workflows around it, are we locked in?

No. The output is structured data with an API and webhooks, so your integrations are yours to keep. And Recap runs on the same conversation intelligence stack as our custom builds — if you eventually want deeper analysis, like sentiment trends across all customer conversations, you graduate on the same foundation.

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