Our Mission

Building the AI employee that reads the room

Revenue teams are drowning in browser tabs, fragmented spreadsheets, and generic AI spam. We founded Dossier to give every sales rep and GTM operator a brilliant, tireless colleague inside Slack who knows their business inside out.

1-2 hrs
Saved per rep every single day
34%
Average increase in meeting hold rate
0 Days
Zero model training on customer data
99.9%
Production SLA uptime commitment
Why We Started Dossier

Stop forcing sellers to be data administrators.

Over the last decade, sales tech became bloated. To prepare for a single 20-minute prospective meeting, an account executive had to open LinkedIn, cross-reference HubSpot or Salesforce, search Google News for leadership changes, look up mutual connections on Attio, and draft an email in Gmail.

The early wave of AI tools made it worse: they flooded inboxes with recognizable, generic AI hallucinations that damaged brand trust.

We built Dossier on a simple premise: what if your CRM, your meeting notes, and live web intelligence were synthesized into a concise morning briefing directly where your reps already collaborate—in Slack—with high-intent drafts ready for one-click review?

Our Core Operating Principles

The architectural convictions behind every line of code we ship.

Human-in-the-Loop Always

AI should prepare the research, draft the outreach, and surface warm intros—but reps always maintain the final click of approval. No silent, unmonitored spam bots.

Model-Agnostic & Zero Lock-In

Frontier LLMs evolve every month. Dossier is built to seamlessly route queries between Anthropic Claude, OpenAI GPT-4o, and enterprise private models without breaking your workflows.

Zero UI Fatigue (Slack Native)

Your team doesn't need an 11th SaaS dashboard to log into. We bring the research, the briefs, and the actions right into Slack where your team is already talking.

Radical Data Sovereignty

Your data is strictly yours. We never train AI models on customer inputs, enforce contractual Zero Data Retention with model providers, and encrypt all data with TLS 1.3 and AES-256.