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Introducing Cell: The Language Layer For Software
A New Interface for Teams to Interact With AI Agents on Any UI - Starting With Data Teams
We’ve all been there—staring at a screen filled with tabs, jumping between clustered dashboards, siloed reports, and your supposed “AI workflow builder fix” to piece together some insights for your team. It’s frustrating and slow, and it kills momentum.
The problem isn’t a lack of tools—if anything, we have too many. The real issue is how disconnected they are. Every time you switch between them, you lose context, focus, and time, wasting time just navigating instead of actually solving problems.

That’s why we built Cell, the language layer for software built by the team at OpenSesame. Cell allows people to interact with a network of AI agents on any UI.
At its core, Cell acts as the interface between your data, APIs, and AI agents. It exists in two form factors:
A full-screen workspace—where teams can analyze, automate, and take action on complex workflows.
An embedded interface—that lives inside your product, enabling customers to interact with your business data effortlessly.
By layering over your existing tools, Cell understands your queries, finds the correct data, and executes the proper workflows.
Why is This Relevant Now?
Over the past few months, we’ve worked closely with teams handling complex workflows, from financial data to SaaS. Their biggest challenge isn’t the complexity of their data; it’s the friction of accessing and acting on it.
Every extra step—every context switch—costs time. Research shows that regaining focus after switching tasks takes 23 minutes. Multiply that across a team, and you’re losing hours every day.
And your customers feel this too. No one wants to dig through reports to find an answer. Every extra click slows decision-making and weakens engagement.
Let’s Take A Real Example
Consider an internal team that needs to gather insights for their end-of-year budget by beginning with an analysis of recent order data from Shopify. Here’s what that process typically involves:
Log into Shopify and figure out what data to analyze.
Manually export the data as a CSV / Make it shared with their team
Format the spreadsheet to make it usable
Build a chart to visualize trends
With Cell:
Every part of the process can be done using natural language.
"Show me recent order history from our Shopify store."
"Turn this into a Google Sheet called ‘Sales Revenue - Recent Orders.’"
If they need more profound insights, they click ‘Visualize,’ and Cell generates an interactive chart—fully clickable and shareable for further analysis

Visualize - Shopify Data
At OpenSesame, we're focused on making AI agents smarter at picking the right tools for the job. One of the biggest challenges with agents today is ensuring AI selects the most relevant tools—not just any available option. Most AI systems struggle with accuracy when the number of tools per query increases.
Cell's Orchestration is built differently. It doesn’t just look at keywords—it understands intent, context, and past interactions to ensure it can select up to four tools per query for the most precise and efficient execution. This prevents unnecessary tool overlap while keeping workflows flexible and effective.
For example, if you ask for the historical price of Bitcoin over five years, Cell doesn’t just pull random numbers. It searches the web for reliable data, extracts structured financial records, formats the results, and generates a graph, ensuring accuracy and relevance for the given query.

Average USD price over each specified year
What We’re Launching Today
This is just the beginning. Today, we’re launching our Alpha program for teams that want to rethink their approach to data management across their workspace.
The first 50 teams will get priority access and direct input into shaping Cell’s development roadmap.
If you’re tired of juggling tools and ready to close those extra browser tabs permanently, we’d like to have you join the Alpha.
Sign up for the waitlist here: Alpha Waitlist
And we’ll touch base as soon as possible regarding the next steps.
We're interested in learning from teams managing complex workflows. We'd like to hear your insights on whether you have fragmented tools, constant context switching, or complex data to act on.
We're researching and would love to chat—Book a call here
Take a look at our launch video below :)