AI Meeting Assistant
In Parallel
In Parallel gives your AI the shared context it needs by automatically capturing meetings, decisions, and plans, and making them available to any AI tool with source-backed answers.
In Parallel
What is In Parallel?
In Parallel is a context layer for enterprise AI that automatically joins meetings, captures decisions and commitments, keeps plans updated, and provides a shared memory accessible by any AI tool via MCP.
In Parallel vs Similar AI Tools
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How to use In Parallel?
- 1Connect your calendar and tools (e.g., Slack, Notion).
- 2In Parallel automatically joins meetings and captures decisions.
- 3Use any AI tool (like ChatGPT, Claude) with In Parallel as context via MCP.
- 4Ask questions and get answers with source citations.
In Parallel Key Features
- Automatically joins meetings and captures decisions and commitments
- Keeps plans up to date without manual intervention
- Provides a shared context layer accessible by any AI tool via MCP
- Permission-scoped access mirroring user permissions
- EU-hosted, GDPR compliant, ISO 27001 and ISO 42001 certified
- Never trains AI on your data
- SSO, RBAC, and audit logs included
In Parallel Use Cases
- The plan that updates itself - plans stay true to reality without manual updates
- The status report that writes itself - promises tracked to done
- The drift alert before the fire drill - spot when reality diverges from the plan
- Keeping all AI tools informed of team context without manual context files
- Reducing time spent chasing context across meetings, threads, and tools
In Parallel Pricing & Free Credits
In Parallel currently operates on a Free, Free Trial model.
In Parallel Pros & Cons
Pros
- Automatically captures meeting context and decisions with little setup
- Works with any AI tool via MCP, avoiding vendor lock-in
- Permission-scoped and secure with EU hosting and compliance certifications
- Saves managers 25-35 hours per month on coordination
Cons
- Pricing may be high for small teams or startups
- Requires integration with existing tools (calendar, Slack, etc.)
- Effectiveness depends on the quality of captured data
What is In Parallel best for?
- Managers and teams using AI tools that need up-to-date shared context
- CTOs and Heads of AI implementing enterprise AI strategies
- COOs and PMOs looking to reduce coordination overhead