The coordination layer
The missing link between
your meetings and your AI.
Your Jira doesn’t know why a decision was made. Your CRM doesn’t know what was promised in the call. Your Confluence page was last updated three sprints ago. None of your operational systems have the context your AI actually needs.
The In Parallel coordination layer captures the richest context in your organisation — live meetings — and makes it available to Claude, Copilot, and ChatGPT instantly. One layer. Every AI tool. 10× the output.
46%
of management time in meetings
95%
of context never documented
0%
of that context reaches your AI
10×
output with organisational context
Your meetings
Zoom, Teams, Meet
Coordination Layer
Decisions, risks, actions,
dependencies — structured
Your AI tools
Claude, Copilot, ChatGPT
The primary context provider
for enterprise AI.
Every enterprise is adopting AI tools. Nobody is solving the context problem. Your people spend hours briefing ChatGPT on things the organisation already knows. That’s not productivity — that’s overhead.
The context gap
Every AI conversation starts
with the same problem.
Your organisation generates hundreds of hours of meeting data every week. Inside that data: decisions, priorities, risks, dependencies, and the real state of every project. But when your people open Claude or ChatGPT, none of that exists.
Without context
General-purpose chatbot
“I can write you a project plan!” — based on generic templates with zero knowledge of your actual situation, team, or constraints.
With copy-paste context
Context window stuffing
Paste a 90-minute transcript into Claude. Wait. Get a summary nobody reads. Repeat tomorrow. 20 minutes of human overhead per meeting.
With In Parallel
Organisational co-pilot
Claude already knows what was decided yesterday, who owns what, and which risks were flagged across every team. Zero briefing time. Full context. Always current.
Why meetings beat operational systems
Jira & Asana
Task status. Not decision context. You know what shipped, but not why it was prioritised, what was traded off, or who committed to the timeline.
→ In Parallel captures the reasoning behind every decision
Salesforce & HubSpot
Deal stages and activity logs. Not what the customer actually said, what concerns they raised, or what was promised on the call.
→ In Parallel captures the actual conversation with full nuance
Confluence & Notion
Documentation that was accurate when someone wrote it. Now three sprints behind reality. Nobody has time to update it.
→ In Parallel is always current — it updates after every meeting
Slack & Teams chat
Unstructured noise. Decisions buried in threads. Context lost in scroll. No AI can reliably extract execution truth from chat.
→ In Parallel structures signals into decisions, actions, risks — automatically
Meetings are where execution truth is created — where decisions are made, priorities shift, and commitments are spoken aloud. No system of record captures this. Until now.
How it works
From meeting to action.
Five steps, zero manual work.
A meeting happens. Context is captured, structured, and shared across the organisation. Your AI tools draw from it to produce documents, plans, and insights — without anyone briefing them.
Capture
01
Meeting happens
Your team meets on Zoom, Teams, or Meet. Our notetaker joins silently — no plugins, no behaviour change. It transcribes the full conversation with speaker attribution in 50+ languages.
Full transcript with speaker IDs
Extract
02
Signals are identified
AI extracts 9 structured signal types from the transcript: decisions, action items, risks, dependencies, escalations, opportunities, learnings, progress updates, and obstacles. These aren't notes — they're execution signals.
Structured observations linked to speakers and topics
Build
03
Context is assembled
Signals flow into a workspace — a shared context space for a team, project, or scope. Each workspace accumulates meeting intelligence over time: what was decided, who owns what, what's blocked, what changed since last week.
Living organisational memory per workspace
Share
04
Workspaces control access
Workspaces determine who sees what. The product team's workspace is separate from the board workspace. Cross-workspace observations surface when teams discuss the same risks or dependencies — but the boundary is controlled.
Governed context sharing across the organisation
Act
05
Context powers actions
Once context is built, every AI tool in the organisation can draw from it. One click in Claude, one prompt in Copilot — and it knows your business. The meeting summary is the beginning, not the end.
Documents, plans, reports, insights — from one prompt
What you get
Not just notes.
Actions ready to go.
After every meeting, your team gets a structured summary with decisions, risks, and action items. Each action is one click away from becoming real work — a follow-up email, a project plan, a battle card, a job description.
Your meeting summary is ready.
Product & go-to-market weekly
Monday, 30 March · 10:00 · sarah@company.com, marcus@company.com, elena@company.com
Summary
- •Platform migration timeline approved for Q3 with phased rollout starting August
- •Enterprise pricing restructure discussed — consensus on value-based tiers but final numbers TBD
- •Customer onboarding bottleneck identified — current process takes 3× longer than target
- •Strong positive signal from Nordic expansion pilot — 4 enterprise leads from first 2 weeks
Key Decisions & Milestones
- • Migration architecture approved with microservices approach — @Marcus → finalise technical spec. Target: This week.
- • New onboarding flow design to reduce time-to-value by 60% — @Elena → prototype and test with 3 customers. Target: 2 weeks.
- • Nordic expansion budget increased based on early results — @Sarah → hire regional lead. Target: End of April.
Action Items
@Marcus → Write technical specification for migration architecture.
Due: Friday
@Elena → Redesign customer onboarding flow to hit 60% time reduction.
Due: 2 weeks
@Sarah → Competitive analysis on Nordic market entrants.
Due: Next week
@Sarah → Draft job description for Nordic regional lead.
Due: End of week
Every action button generates a complete first draft using full meeting context — decisions, discussion points, and tone. Ready for review in seconds, not hours.
50+
work types recognised
Emails, specs, plans, battle cards, OKRs, job descriptions, surveys, and more
1 click
from decision to draft
Full meeting context is passed to the AI automatically — no copy-paste, no briefing
90%
less post-meeting admin
Follow-ups, status updates, and documentation happen automatically
Workspaces
Context shared right.
Not shared everywhere.
Every team, project, or initiative gets its own workspace — a governed context boundary. Meetings feed into the right workspace automatically. Your AI only sees what it should see.
Example: Scale-up with 4 workspaces
Product Team
Sprint planning, product reviews, design syncs
Sales & GTM
Pipeline reviews, deal strategy, marketing syncs
Leadership
Management team, strategy sessions, board prep
Board & Investors
Board meetings, investor updates, governance
Cross-workspace intelligence
When Product and Sales both flag the same platform dependency in separate meetings, the Leadership workspace gets an automatic observation. Silos stay intact for day-to-day work. Cross-cutting signals surface automatically.
Meetings → workspaces
Each meeting is assigned to a workspace automatically based on calendar context. Recurring meetings learn their workspace after the first assignment.
Access follows roles
A product engineer sees their team workspace. A COO sees all workspaces. A board member sees the governance roll-up. Access is role-based, not all-or-nothing.
AI respects boundaries
When Claude queries context via MCP, it only receives data from workspaces the user has access to. No data leakage. No privilege escalation. Enterprise-grade from day one.
What context unlocks
One prompt. Full organisational context.
Once context is built from your meetings, here’s what becomes possible — in Claude, Copilot, or ChatGPT — with a single prompt.
Documents
Board pack
Generate a board-ready report from the last 4 weeks of leadership meetings. Evidence-based, not curated fiction. Includes decisions made, risks flagged, and execution health per scope.
"Draft the March board pack from this month's leadership meetings"
Weekly digest
Auto-generated summary of what changed across all workspaces this week. Sent to Slack, email, or wherever your team checks in. No one has to write it.
"What happened this week across all scopes?"
Stakeholder update
Pull context from the relevant workspace and generate a tailored update for investors, partners, or customers — with the right level of detail and framing.
"Write an investor update based on the last quarter's product and sales meetings"
Execution
Living execution plan
The plan writes itself from meeting signals and updates after every meeting. Priorities, ownership, risks, milestones — always current, never manually maintained.
"Create an execution plan for the market entry initiative from the last 3 strategy meetings"
Action item tracking
Every commitment made in every meeting is captured with owner, deadline, and source. No more "I thought you were handling that."
"What's overdue across the product team's workspace?"
Risk register
Risks mentioned in meetings automatically populate a living risk register. Track escalation curves over time — see if a risk is growing or being resolved.
"Show me all open risks across the engineering and ops workspaces"
Intelligence
Cross-team dependencies
Detect when two teams are discussing the same blocker independently. Surface dependencies that live in conversations, not in Jira tickets.
"Which teams are blocked on the same thing right now?"
Decision audit trail
Every decision is logged with who made it, when, in which meeting, and what evidence was discussed. Full traceability without anyone filling out a form.
"When did we decide to change the pricing model, and what was the reasoning?"
Organisational diagnostics
Score meeting quality, decision velocity, and coordination health across the organisation. Detect patterns that no single meeting reveals.
"How has decision quality changed in the sales team over the last 8 weeks?"
Personal productivity
Meeting prep
Before your next meeting, get a pre-read: what was decided last time, what's unresolved, who committed to what, and what changed since then.
"Prep me for the 2pm product review — what do I need to know?"
Context catch-up
Missed a meeting? Or three? Get the full picture in 30 seconds instead of scheduling follow-ups with people who are too busy.
"What did I miss in the platform team meetings this week?"
Presentation builder
Turn meeting context into slides. The AI pulls the right data from the right workspaces and builds a presentation that reflects what actually happened.
"Build a presentation on our Q1 progress from the OKR review meetings"
Not another note-taker
Notes are the input.
Organisational intelligence is the output.
Everyone has a meeting transcription tool. Nobody has an enterprise context layer. That’s the gap we fill.
Granola
Notes for vibe coding
Individual productivity tool. No team context, no cross-meeting intelligence, no organisational layer. Your notes exist in isolation.
In Parallel
Notes for future work — connected to teams, projects, and execution plans across the organisation.
Otter / Fireflies
Meeting transcription
Transcription is a commodity. They tell you what was said. They don't connect it to anything or tell you what it means.
In Parallel
Transcription is the input, not the output. We extract structured intelligence and feed it to your AI tools via MCP.
Notion AI / Confluence AI
AI on your docs
Only knows what's written down. Meetings — where 46% of management time goes — are invisible. Most organisational knowledge never makes it to a wiki.
In Parallel
Captures the 95% of organisational context that never gets documented. Your AI finally knows what's actually happening.
What leaders say
Built for how scale-ups
actually operate.
We were spending 4 hours a week just keeping our AI tools briefed on what happened in meetings. Now Claude already knows. Our product team generates first drafts of specs, emails, and competitive analyses directly from meeting context. The ROI was obvious within the first week.
VP of Product
B2B SaaS, 120 employees · Helsinki
Granola was great for personal notes. But when I needed my COO to see what happened in a meeting she missed, or my AI to know about a decision from last Tuesday, it couldn’t help. In Parallel solved the organisational layer we were missing.
CEO & Co-founder
Series A fintech, 45 employees · London
The action buttons in meeting summaries changed everything. After a 30-minute product review, my team has draft specs, follow-up emails, and project plans ready to review — not in a day, in minutes. It’s like having a chief of staff for every meeting.
COO
Growth-stage marketplace, 200 employees · Stockholm
The T&Cs aligned with what we already had for Claude Enterprise, so legal review was straightforward. One MCP connection covers all our AI tools, and the workspace model gives IT the access controls we need. Smooth procurement process overall.
CTO
Enterprise SaaS, 350 employees · Berlin
For COOs & operations leaders
Your people adopted AI. Now make it work for the organisation.
Individual AI adoption is easy. Organisational AI leverage is hard. That’s where the real ROI lives.
Execution visibility
See the real state of execution across every team — from meeting data, not status reports. Know what was decided, what’s blocked, and where coordination is breaking down.
Living execution plans
Execution plans that update themselves after every meeting. No more asking people to update project tools. The plans stay current because the data flows automatically.
Board materials in minutes
Generate board packs from actual meeting data. Evidence-based, not narratively curated. One prompt, minutes instead of days.
Coordination tax reduction
When AI knows the organisational context, teams stop duplicating work, stop relaying information manually, and stop scheduling meetings just to share what someone else already discussed.
For CTOs & IT leaders
Enterprise AI governance
without the enterprise friction.
Terms you already have
Our T&Cs match Claude Enterprise, Google Workspace, and Microsoft 365. If you’ve approved those, approving In Parallel is the same paper. No new legal review cycle.
One integration, all AI tools
Deploy once via MCP. Works with Claude, Copilot, ChatGPT, and Gemini simultaneously. No per-tool integration. No duplicate IT validation.
Data governance built in
EU data processing. Full DPA. GDPR compliance. Your data never trains third-party models. Role-based access controls on which context flows where.
Shadow AI, solved
Instead of blocking AI usage, give people a governed channel for organisational context. Uncontrolled copy-paste into ChatGPT stops when there’s a better way.
For founders & CEOs
Scale-up speed. Enterprise control.
You’re scaling from 30 to 300 people. Communication patterns that worked at 30 are already breaking. You can feel it. You just can’t see it.
The management operating system
Teams can query Claude about cross-functional priorities. You can generate execution plans from real meeting data. The AI becomes your management co-pilot — not just a writing assistant.
Investor-grade visibility
Board materials, strategy validation, and execution health — all derived from actual organisational data. Investors see evidence, not narrative.
Deploy in a week
No IT project. No change management. Our bot joins your meetings. Context flows to Claude via MCP. Your team notices their AI got smarter. That’s it.
Modern work, not old work improved
We’re not digitising your existing processes. We’re building the coordination layer that modern AI-first organisations will run on. You’re not buying a tool — you’re adopting the operating model.
Simple pricing
2× the cost. 10× the output.
If your Claude seat costs €30/month, In Parallel adds roughly €30/month. The AI you’re already paying for becomes dramatically more useful.
Team
Scale-up
Up to 50 users. Meeting context, team structure, and execution plans via MCP. Perfect for growing teams that want AI leverage from day one.
Start a pilotOrganisation
Enterprise
Unlimited users. Full context layer with governance controls, SSO, audit trails, and dedicated onboarding. For organisations serious about AI-first operations.
Talk to usAdd-on
Diagnostics
Add 20 organisational diagnostics on top of the coordination layer. Continuous monitoring, longitudinal scoring, and strategic health reporting.
Learn moreQuestions we hear
Frequently asked questions.
How does the MCP integration work?
MCP (Model Context Protocol) is the open standard for connecting AI tools to external data. We provide an MCP server that Claude, Copilot, and other AI tools connect to. Your AI tool requests context — "what happened in the ops meeting?" — and our server delivers structured intelligence. No browser extension, no copy-paste, no context window stuffing.
Which AI tools do you support?
Any tool that supports MCP: Claude (Desktop, Code, and Enterprise), GitHub Copilot, Cursor, Windsurf, and more. ChatGPT and Gemini support is available via API integration. We are platform-agnostic — your organisation can use multiple AI tools simultaneously.
How is this different from just pasting transcripts into Claude?
Context window stuffing gives you a wall of text with no structure. We extract 9 structured signal types from every meeting, connect them to teams and projects, track them longitudinally, and deliver precisely the context your AI needs for the task at hand. It's the difference between dumping a filing cabinet on someone's desk and having a research assistant who knows everything.
What about data security and privacy?
Enterprise-grade from day one. Data processed and stored in the EU. Full DPA and GDPR compliance. We match Claude Enterprise, Google Workspace, and Microsoft 365 terms and conditions. Your data never trains third-party models. SOC 2 Type II in progress.
Will my team actually use this?
The deployment model is "install and forget." Our meeting bot joins calls automatically. Context flows to AI tools via MCP without any action from users. The most common reaction from teams is surprise at how much their AI suddenly knows — followed by "why didn't we have this before?"
What does "2x cost, 10x output" mean concretely?
A Claude Enterprise seat costs roughly €30/month. In Parallel adds roughly €30/month per user. But without organisational context, Claude is a general-purpose assistant. With it, Claude becomes an organisational co-pilot that knows your meetings, your projects, your team structure, and your execution state. The productivity multiplier comes from eliminating the hours spent briefing AI on context it should already have.
How long until we see value?
Week one: meeting summaries and searchable context. Week two: cross-meeting intelligence and team-level observations. Week four: execution plans, longitudinal patterns, and organisational diagnostics. The system gets more valuable with every meeting recorded.
Can IT control what data flows to which AI tools?
Yes. The admin layer gives IT full governance over which context is available to which tools, which teams have access to which data, and what security policies apply. We provide the controls enterprise IT needs without slowing down the people who need to work.
Your AI is already paid for.
Make it worth it.
We connect to your meetings, structure the context, and deliver it to Claude via MCP. Your team’s AI goes from generic assistant to organisational co-pilot — in one week.
Live demo on your own meetings. No commitment. Deployed in days, not months.