Your AI is great, but it doesn't know what your team decided last Tuesday.
Without context, your AI just gets it wrong faster. In Parallel gives your AI the shared context you already have: the decisions, threads, and meetings it's missing, with the source behind every answer.
Works in Claude, Gemini, ChatGPT, and Copilot — nothing new to learn. 
Before & after
From scattered tools to one shared picture.
Meetings, threads, and the tools you already use — captured automatically and kept current, so nothing important stays trapped in one place.
Run the org on live memory, not curated decks.
Org-wide rollups update themselves — and the AI you run on top answers from live decisions, with the source behind every number.
Why a context layer
Not chat memory. Not a context file. Your company's memory.
Built-in memory
Per person, per tool. What one person teaches Claude, ChatGPT never hears — and the team never sees.
vs. AI memoryContext files
A CLAUDE.md is frozen the moment it's written. Nobody maintains it, so everyone quietly stops trusting it.
vs. context filesIn Parallel
Shared, live, and sourced. Captured where work happens, current on its own — and your AI only sees what you can see.
Explore the context layerOne memory for every AI tool.
Works with the rest of your stack
In Parallel gives your AI the context to do real work — and only ever sees what each user can see. Your company's memory is yours: it works with every AI tool and isn't locked to any of them.
Permission-scoped EU-hosted Never trains on your data
How it works?
In Parallel listens where work happens — and captures every decision as it's made.
joins your meetings
reads your Slack & Teams threads
…and any other tool you need.
In Parallel gives your AI the context and deep understanding you need to do your work better. Execution plans
Updated just now
Customer insights
Updated just now
Decisions & commitments
Updated just now
Use cases
Put your organisation's memory to work — in whatever tools you already use.
Built for teams putting AI to work — CTO & Head of AI, COO & PMO, and everyone whose work runs through AI.
Job 01
The plan that updates itself
Plans stay true to reality without anyone updating them.
Job 02
The status report that writes itself
What people promised in meetings, tracked to done — status assembled, not chased.
Job 03
The drift alert before the fire drill
Spot when reality diverges from the plan — while it's still cheap to fix.
The payoff
Hours back. And answers you can trust.
back per manager, every month
No longer lost chasing the right context across meetings, threads, and the tools you already run.
answers you can act on
Work isn't redone, and the wrong answer doesn't ship downstream.
Your data, your rules
EU-hosted. Enterprise-grade. Secure by default.
Built and hosted in the EU — your data never crosses borders without your say. GDPR compliant, ISO 27001, ISO 42001 and SOC 2 Type II certified. No AI is trained on your data. SSO, RBAC, audit logs, EU data residency, and DPIA documentation included from day one.
Security overview
Priced per user. Volume and duration earn the discount.
41% of the work week goes to coordination. In Parallel gives it back.
Plans + everything
€69
per user / month
- Full product free for 20 days — unlimited workspaces.
- Volume + duration discounts apply — down to €39 at 10,000 paid users on multi-year.
- Passive users (no usage) not invoiced.
- Enterprise terms available for over 100 users — SSO, SCIM, custom retention.
Before you ask
The questions every team asks first
- What is In Parallel, exactly?
- The context layer for your company's AI. In Parallel joins your meetings, captures decisions and commitments as they're made, keeps plans up to date automatically — and gives every AI tool you already use the same shared context via MCP, with a source behind every answer.
- How is this different from ChatGPT or Claude memory?
- Built-in memory is personal and locked to one vendor — what one person teaches Claude never reaches ChatGPT or a teammate. In Parallel is shared team memory: captured once, current on its own, readable by every AI tool over MCP. In Parallel vs built-in AI memory →
- How is this different from a CLAUDE.md or context file?
- A context file is a snapshot — accurate the day it's written, stale by the next sprint, and maintained by hand. In Parallel stays connected to where work happens, so the context your AI reads is live, permission-scoped, and sourced. In Parallel vs context files →
- How do I know the context is current?
- Because nobody has to remember to update it. Decisions are captured where they're made, every record carries when it happened and the meeting it came from, and anything your team knows is wrong can be corrected in place — by a person or by your AI. How your context stays current →
- Who can see what?
- Access mirrors your permissions. Workspaces are the unit of trust — each one is a separate MCP endpoint with its own data perimeter — so your AI only ever sees what the person asking can see.
- Is our data safe?
- In Parallel is built and hosted in the EU, GDPR compliant, and ISO 27001, ISO 42001 and SOC 2 Type II certified — with SSO, RBAC, and audit logs from day one. No AI is trained on your data.
One shared reality between your people and your agents.
Get your team and your AI working from the same context.
- Secure
- Share with control
- Always up to date
- Wherever you already work
- Every answer sourced