Product Description

Effective June 2026

Executive Summary

Modern organizations are full of plans, tools, and meetings—but short on shared execution reality.

  • Goals live in OKR tools.
  • Work lives in project systems.
  • Decisions are made in meetings.
  • Status is reconstructed afterward through decks, spreadsheets, and chat threads.

This creates a persistent coordination tax—time spent chasing updates, reconciling versions, and rebuilding shared understanding. Execution does not fail because of missing effort or data—but because reality changes faster than manual coordination can keep up.

In Parallel removes this tax.

It is the missing layer between your AI tooling and your organization: it turns every meeting into structured execution data, keeps a plan current for every Workspace, and exposes that shared context to the AI tools your teams already use.

What the Product Does

In Parallel turns meetings and system updates into a shared reality of execution—and makes that reality available to people and AI alike.

It:

  • joins meetings and captures decisions, actions, risks, and dependencies,
  • reconciles changes from connected tools,
  • keeps an up-to-date execution plan for every Workspace,
  • surfaces drift before it becomes a miss,
  • and exposes the resulting organizational memory to any AI assistant via MCP.

All under manager control.

Core Features

In Parallel is organized around a small set of features. A Workspace is the unit everything is scoped to—a team, project, initiative, or account.

Notes — meetings become execution data

Every meeting makes the next one more useful.

The In Parallel recorder joins every call silently across Zoom, Teams, and Meet and transcribes in 50+ languages. Rather than a flat recap, it extracts structured Findings:

  • action items, decisions, risks, learnings, open questions, and opportunities.

Each Finding links back to its source and to the Workspace, building a living map of how the organization actually operates.

Plans — the plan that keeps up with reality

One self-updating execution model per Workspace.

Each Workspace has an execution plan that maintains itself from meeting Findings and connected tools. It:

  • shows goals, priorities, tasks and milestones, risks and dependencies, and explicit ownership,
  • recalculates dependencies when reality shifts,
  • detects drift the moment it appears,
  • and stays in sync with delivery tools like Jira through MCP—your AI assistant keeps the board and the plan aligned.

What gets decided in a meeting becomes a proposed Workspace and plan update you review and confirm right after the meeting—nobody rebuilds the plan by hand.

MCP — shared context for every AI

The shared context layer for every AI in your stack.

Everything In Parallel captures—decisions, plan state, owners, drift signals—forms an always-on organizational memory. Through the Model Context Protocol (MCP), that memory is exposed to Claude, ChatGPT, Cursor, and other tools, so they all draw from the same source of truth instead of guessing. AI stops being smart-but-blind and becomes grounded in real execution context.

The Platform & AI

AI Intelligence Layer

Summarizes conversations, detects drift and anomalies, ranks priorities, and drafts insights. Every output is explainable—each recommendation links back to its source.

Data & Knowledge Layer

Connects people, metrics, and decisions in a live graph. What was once “lost in slides” becomes a searchable, AI-accessible knowledge fabric.

Integration Layer

Two ways in, no heavy migration. Direct integrations capture signal from the tools you already run—Calendar (Google or Microsoft), Gmail, Slack, and Microsoft Teams. And the Model Context Protocol (MCP) acts as a universal integration layer: an AI assistant like Claude reaches into In Parallel’s context and out to your delivery tools—for example, keeping a Jira board in sync with the execution plan—so you connect systems through MCP rather than building point-to-point integrations. Other integrations are available based on customer need.

Governance by Default

One accountable owner per Workspace, explicit ownership everywhere, role-based access control (RBAC), and certification to ISO/IEC 27001, ISO/IEC 42001, and SOC 2 Type II. Every execution snapshot is attributable and defensible. Trust isn’t an add-on; it’s the foundation.

Who It’s For

In Parallel is for managers who own outcomes, even when they don’t control all the work—across every function:

  • Executive, Finance, and HR & Culture (run the org),
  • Product, Engineering, and Operations & PMO (build & ship),
  • Sales and Marketing (go to market).

Individual contributors don’t need licenses and benefit automatically.

In Closing

Management has long meant translating between meetings, tools, and people.

In Parallel removes that burden. When the plan stays truthful by default and shared context is one query away:

  • coordination drops,
  • decisions compound,
  • and leadership time shifts back to judgment and direction.

In Parallel does not replace leadership. It gives leaders—and their AI—a management system that keeps execution reality aligned, quietly, continuously, and at scale.