Product
The agent that helps, measures, and protects.
OLi is a desktop AI agent that acts on the work itself — no prompting, no waiting. It shows up in the moment with the right help, records what actually happened through the activity graph, and keeps every tenant’s data inside its own boundary. Three capabilities, one agent, one substrate.
Deploy directly: 10% more productive time in 30 days, guaranteed.
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Pillar 1 · Help
Help in the moment.
OLi recognizes the work and surfaces the right thing the moment it matters. Today, mostly content — micro-learning when a skill gap is detected, a knowledge-base article when the task calls for one, a break reminder when continuous focus patterns warrant it. In production for more than five years.
Increasingly, skills — real actions OLi takes for the user. Generate SOWs from a timesheet and send them for signature via Zoho Sign. Record insurance eligibility into an EHR. Summarize an email thread grounded in your work context. Same agent, same triggers — and a growing list of things it can do.
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Content — shipping today
Micro-learning, motivation, knowledge-base articles, break reminders, coaching nudges. Multi-tenant, in production.
Skills — rolling out now
Tenant-customized actions wired to your stack. Built by Dataken engineering today. Self-serve Skills API coming soon.
Pillar 2 · Proof
Proof of where work really happens.
Analytics, process mining, and the OLi Analyzer — the only view of work built from the activity graph. Not surveys. Not self-reports. Not time-tracking that depends on people remembering to click a button. The record of what actually happened.
What the graph can prove
- Where time actually goes, across apps and tasks.
- Which processes break, and at which step.
- Whether an OLi intervention actually changed behavior.
Where does the time actually go?
Illustrative. The activity graph records what actually happened. Self-reports, surveys, and time-tracking tools that depend on people remembering to click a button don’t.
Pillar 3 · Privacy
A privacy story your security team will sign.
This isn’t a disclaimer. It’s architecture. Four layers, enforced at the data and system level — not promised in a marketing page or bolted on as a policy overlay.
Every tenant gets its own graph, its own rules registry and its own inference boundary. Cross-tenant data sharing isn’t a feature you have to opt out of — it isn’t possible.
On-device capture
Raw activity is processed on the user's machine. Only structured records leave the device.
Anonymization at the data layer
Anonymized on ingest as an architectural property, not a policy overlay.
Privatized LLM inference
Zero retention. No training on tenant data. Open-source isolated deployment available for security-sensitive tenants.
Per-tenant boundary
Your rules registry, skills, and activity graph are isolated to your tenant. Cross-tenant data sharing is not a feature.
End-to-end
One agent. One graph. One coherent story.
Each pillar above links to a deeper page: the moat that makes all three possible, the mechanism underneath, and the outcomes they drive.
The moat
The missing-axis argument
Why activity context is a separate axis from RAG, and why Dataken is the only one operating it in production.
Read moreThe mechanism
The five-step loop
Capture → Graph → Recognize → Act → Learn. The activity graph runs through every step.
Read moreThe impact
The outcomes it drives
Productive time recovered, engagement raised, behavior changed — measured, not estimated.
Read moreOne agent. One graph. Three capabilities no one else has together.
10% more productive time in 30 days. Guaranteed when you deploy directly.
Book a scoping callWhat buyers ask about OLi
Frequently asked
What does OLi actually do?
OLi is a desktop AI agent that recognizes what a person is working on and delivers the right knowledge, micro-learning, or completed action at that moment — before they ask. It reads the Dataken activity graph, a first-party record of real desktop work that has run in production since 2020 across more than 10 billion activity records.
Is OLi employee monitoring software?
No. Monitoring tools exist to report on people to their managers. OLi exists to help the person doing the work in the moment, and its analytics describe processes rather than individuals. Activity is anonymized at capture rather than masked afterward, inference runs inside a per-tenant boundary, and consent is captured at install. The architecture is built to be reviewed by security and compliance teams before deployment.
What is task mining, and does OLi do it?
Task mining is the measurement of how work is performed at the desktop level — which applications are used, what steps are taken, how long each takes, and how much that varies between people doing the same job. Yes: task mining is what builds the Dataken activity graph, and it is the foundation every other OLi capability runs on.
What does OLi run on?
Windows and macOS desktops. OLi captures application and window context rather than integrating with each application individually, so specialized software — industry-specific and line-of-business tools — is captured without per-application integration work.
How is OLi priced, and what is the guarantee?
There are two ways to start; choose one. Most customers start with a fixed-fee assessment measured at the desktop. The smallest is the Single-Team Snapshot ($4,950, one team up to 15 seats, 2 weeks, written report), which is fully credited toward a bigger assessment if you go further. Above it: a Workforce Assessment ($12,500, one team up to 40 seats, 3 weeks), an AI & Automation Assessment ($15,000, up to 75 seats, 4 weeks), or both ($22,500, up to 75 seats, 4 weeks). Enterprise programs (more than 75 seats or 3+ sites) start from $25,000, and private equity firms can assess up to three portfolio companies for $55,000. 100% of the assessment fee is credited toward the first-year OLi deployment if you sign within 60 days of the readout. Customers who would rather skip the assessment can deploy OLi directly, and that path carries the guarantee: 10% more productive time in 30 days, measured against a baseline agreed at kickoff. The guarantee does not apply to the assessment, or to a deployment that follows one.