When people sign off for the day, their context goes with them. When they're on leave, or switch projects, or move to different teams, the knowledge they've built up becomes inaccessible to everyone else.
You've probably experienced this yourself. You're working on something and you need to know why a decision was made, or what feedback led to a feature change, or whether someone's already tried the approach you're considering. The information exists somewhere, but finding it means interrupting colleagues, searching through multiple tools, or just making your best guess and hoping for the better.
We built Rice to solve this problem.
Introducing Rice: Context That Stays When People Leave
Rice creates what we call AI shadows for your team. Think of them as context layers that learn from how people work and make that knowledge available to everyone who needs it.
Here's how it works in practice. Sarah from your product team is creating tickets for new features. Normally, she'd need to wait for her teammate to upload notes from customer interviews to Notion, or she'd need to schedule a call to get the context. With Rice, that information surfaces automatically as she's working. She sees the relevant feedback from last week's interviews right when she needs it.
Or take this scenario: a developer is working on a new feature and needs to understand why a particular API endpoint was designed the way it was. The engineer who built it is on leave. Rice surfaces the technical discussion from when that decision was made, including the trade-offs considered and the customer requirements that influenced it.
The difference is that Rice doesn't require anyone to change how they work. It learns by integrating with the tools you already use: Slack, Jira, GitHub, your calendar, and others. Plus our desktop app, which captures additional context when needed (with full privacy controls that we'll talk about in a moment).
Why This Matters Now
Remote and distributed teams have made this problem more acute. When your London team starts work, they need to know what your San Francisco team discussed overnight. Currently, that means reading through Slack channels or waiting for summary emails.
With Rice, the context is just there. Not as a wall of messages to wade through, but as relevant information surfaced when it's needed.
The same applies across different scenarios:
For cross-functional work: Marketing can see that a feature they're planning to highlight in a campaign was actually deprioritised last sprint, before the campaign goes live.
For customer support: When a customer asks why something works a certain way, support can instantly access the engineering discussion that explains the reasoning, plus any customer feedback that influenced the decision.
For onboarding: New hires can see the history of how decisions were made and why, instead of spending months absorbing tribal knowledge through osmosis.
For knowledge preservation: When someone leaves the company, their expertise doesn't disappear. Rice has already captured the reasoning behind their decisions and the context around their work.
For compliance: You have a clear trail of who knew what and when, without requiring manual documentation.
For strategic planning: Leadership can quickly surface patterns across customer feedback, market signals, and internal discussions without manually synthesising information from dozens of sources.
We'll be writing dedicated posts about each of these use cases. Subscribe to follow along.
How Rice Actually Works
Rice builds what we call a temporal knowledge graph. Unlike traditional knowledge bases that capture information at a single point in time, Rice tracks how information evolves. It knows when decisions change, how contradictions get resolved, and why priorities shift.
This temporal layer is crucial. It's not enough to know that someone decided X. You need to know they decided X in March based on certain customer feedback, then adjusted to Y in June when market conditions changed. Rice tracks all of that automatically.
The system is proactive rather than reactive. Instead of waiting for you to search for information, Rice surfaces relevant context based on what you're doing. When you're in a particular Jira ticket, or drafting a particular email, or preparing for a specific meeting, Rice knows what context matters for that moment.
Privacy and Control
We know this raises questions about privacy. Fair enough. Here's how we handle it:
All data is encrypted end to end. The desktop app processes information locally and never stores or transmits raw screenshots. Only anonymised, structured context is used. You can pause or disable the desktop app anytime.
More importantly, Rice respects your organisation's existing permission structures. If someone doesn't have access to certain information in your current systems, Rice won't surface it to them either. Confidential information stays confidential.
You also control how your AI shadow responds. Through custom interaction instructions, you can set boundaries on what your shadow shares. For example, if you're in Finance, you might configure your shadow not to answer budget questions from other teams, or to redirect them to speak with you directly for sensitive matters.
What Makes Rice Different
We're not trying to replace your existing tools. Slack, Notion, Jira, and others all serve important purposes. Rice sits on top of them, connecting the context between them.
The key difference is that Rice learns automatically from how work actually happens, rather than requiring people to manually maintain documentation. Every knowledge management system starts with good intentions, but they all face the same problem: they only work if people consistently update them. And people are busy.
Rice removes that requirement. It captures context as work happens, without anyone needing to think about it.
Our technology is also built differently from the ground up. The temporal graph infrastructure we've developed can't simply be added to existing tools. It requires fundamental architectural decisions that we made from day one.
Finally, Rice gets more valuable over time. The longer your organisation uses it, the richer the knowledge graph becomes. Six months of organisational memory creates compound value that's irreplaceable.
Who We Are
Rice is built by founders with prior venture-backed AI experience and exits. We're supported by advisors with deep enterprise expertise in operations, manufacturing, and defence consulting. We're based in the UK and working with companies ranging from 100 to 1,000 employees across technology and professional services.
Getting Started
Rice takes about 10 minutes to integrate and starts providing value immediately. We're currently running pilot programmes with committed success metrics.
If you're interested in seeing how Rice works for your team, book a demo
What's Coming Next
Over the next few weeks, we'll publish deeper explorations of specific use cases:
- How engineering teams prevent repeated incidents using buried context
- Reducing onboarding time by giving new hires instant access to institutional memory
- Enabling every sales rep to have full customer context automatically
- Maintaining strategic continuity when key people leave
- Building audit trails without manual compliance documentation
Follow our blog to see how Rice applies to your specific role and industry.
