Enterprise software
that runs itself.
Most enterprise software is a human workflow with a chatbot strapped on top. We are designing in the opposite direction. Every function we build runs as an autonomous loop. The interface is the exception path. The default is the system, running.
Active bets
05
Parent platforms
05
Posture
Building in public
Backed by Taqtics product platforms in production across
The Thesis
The unit is not the app.
It is the loop.
The old SaaS contract was simple: pay for an interface that helps a person do a job faster. AI does not just make that person faster. It removes the requirement that a person be in the loop at all. We are designing the next generation of enterprise software around that fact.
Each system we ship has five moving parts. Together, they form a loop that runs on its own. People show up only when the loop hits an edge it cannot resolve. The interface is for those edges. The loop is for everything else.
We spend tokens, not headcount. We record every cycle as data. The loop tightens itself, week by week.
→ This is what we mean when we say AI-native.
The Loop
Sense
Capture the signal where it actually happens.
Decide
Apply the rules of the business, encoded.
Act
Use the tools your stack already runs.
Verify
Prove the action with evidence.
Learn
Sharpen the loop with every cycle.
The Bets
Five loops we are wiring up right now.
Each bet replaces a category of enterprise software with an autonomous loop. Some are in production with existing Taqtics customers. Some are research today and production tomorrow.
Task & Ticket Workflows
Operational tickets that triage, route, and close themselves.
AI Visual Merchandising & Shelf Analysis
Every shelf, every store, every hour — judged against the planogram by an agent that has seen it.
Shift Management
Schedules that forecast, fill, and adapt without a planner.
ESG Reporting
ESG signals captured at site level, verified by agents, board-ready by quarter-end.
AI-Native Platform for Retail & QSR
An operating system for the floor, with every function running as its own loop.
How the Lab operates
Small team.
Disproportionate output.
We are not selling more SaaS seats into the operations org. We are replacing whole categories of operations software with loops that run themselves. That changes how a small team can compete.
- 01
We spend tokens, not headcount
The work that used to require a team of analysts, coordinators and reviewers runs as compute. The team we keep is the team that designs new loops.
- 02
We record every cycle as data
Every decision the loop makes is logged with its inputs and outputs. The data set we accumulate is the moat. Each cycle makes the next one sharper.
- 03
We do not replace your stack
The loops we build connect to the systems you already run — POS, ERP, HRMS, CCTV, ticketing. We meet your data where it lives.
- 04
We treat humans as the exception path
When the loop hits an edge it cannot resolve, a person shows up. That is the interface. The rest of the time, the system runs.