Paperstar
Echo provides AI agents that live inside the tools teams already use—Slack, email, Linear, and Codex—to learn company-specific workflows and execute tasks end to end. The agents watch how work moves through existing tools, then pick up the next step the way the team would, from incident response to deal desk approvals. Echo agents are team-owned, not personal, so anyone can teach them and the know-how stays with the company.
- AI Agents
- Wellness & Fitness Technology
- Artificial Intelligence
- Enterprise Software
- Software Only
- Data & Analytics
- Digital Health
- Healthcare Technology
Funding
Founders
Founder details are not available yet.
Product
Problem
Teams lose time switching between communication tools and specialized AI assistants, forcing them to manually copy context and re-explain company-specific knowledge. Generic AI tools lack access to the institutional history, workflows, and approval processes that shape effective decisions, leading to generic or off-brand responses that require significant human review.
Solution
Echo provides AI agents that live directly inside the tools teams already use, including Slack, Gmail, Google Drive, Notion, Calendar, Linear, and GitHub. The platform ingests a company's context—its knowledge, history, and details—so agents can answer questions and draft responses with full situational awareness. Teams define their own rules, tone, workflows, and approval boundaries, ensuring AI output aligns with company standards. Echo agents are team-owned rather than personal, meaning anyone can teach them and the institutional know-how stays with the company. The agents learn continuously by watching what team members edit, approve, and ignore, and they score their own work against custom evals to fix their own misses. Users can select preferred models from providers like Claude and OpenAI, and connect additional tools through MCP integrations and custom APIs.
Target Audience
Primary users are operations, sales, engineering, and deal teams at mid-to-large companies that need AI assistance grounded in company-specific context and integrated into their existing collaboration stack.
Features
- Native integrations with Slack, Gmail, Google Drive, Notion, Calendar, Linear, Google Docs, GitHub, Google Sheets, Fathom, Ashby, and more
- Company-specific context ingestion that captures institutional knowledge, playbooks, and historical details
- Configurable rules engine for tone, workflows, and approval processes (e.g., "Finance signs anything over $20k")
- Team-owned agent architecture where anyone can teach the agent and everyone benefits
- Self-improvement system that scores its own work against custom evals and drafts fixes for misses
- Multi-model support including Claude and OpenAI with user-selectable options
- MCP tool compatibility and custom API connections for extending agent capabilities