Infinity Square Labs builds software with AI agents that plan, write, test and review code every day, under human direction and sign-off. We put document intelligence and on-device processing into our own products, and we turn business data into decisions you can defend.
Agents build. Models understand. Analytics measure. Each feeds the next, which is the infinity in our name.
ES-083Clickable links while signingPlan
Plan
Build
Test
Review
Ship
Example · one feature, one loop
01
Agentic engineering
We run teams of AI agents that take a specification, write the code, write the tests, review each other's work and raise what they can't resolve. People set direction, review findings and approve every release.
Daily build cycles against a feature register
Independent agent review before anything ships
Full audit trail of every change
0 fields · 0 people
SignatureLandlord0.99
SignatureTenant0.99
Full nameLandlord0.97
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Date signedLandlord0.98
Date signedTenant0.98
Example · fields placed on upload
02
Document & data intelligence
Models that read real documents: finding the signature lines, dates and parties in a contract nobody formatted for a machine, extracting what matters, and running where the data already is, often entirely in the browser.
Field detection and document understanding
OCR and extraction on the user's device
Evaluated on held-out documents, not demos
Weekly active · 90-day forecast · example12,480range 11,700 – 13,300
BasePrice +5%New market
The shaded band is the likely range, not a promise. Scenarios re-run the same model with one input changed.
Example · illustrative figures
03
Analytics & decision systems
Data platforms, forecasts and dashboards built to answer a specific decision, with every metric defined and owned. We show the likely range of outcomes rather than a single confident guess.
Pipelines and a single modelled source of truth
Forecasting, scenarios and pricing analysis
Privacy-first product analytics and experiments
How we build
Built by agents. Answered for by people.
Every working day our agents pick up the next batch from the plan, build it, test it end to end and hand it to a separate reviewing agent that tries to break it. Findings become tickets. Nothing reaches production without a person reading the result and approving the release.
PlanThe register says what is next and why.
BuildAgents write the code and the tests together.
VerifySuites, browsers and real files, every run.
ReviewAn independent agent hunts for failures.
ShipA person approves. The loop starts again.
build board · one day · example
PlannerDay 8 · 30 featuresfrom the register, overdue first
Builder AFields & detectionqueued
0 tests · queued
Builder BAgreement intelligencequeued
0 tests · queued
Builder CAdmin & workflowsqueued
0 tests · queued
Reviewer · independentTries to break it
waiting for builders…
0 findings · 0 held back
A personReads the review. Decides.nothing ships without this stepApproved · deployed to test
Products
Where the research meets a Tuesday afternoon.
We run our own products, so every method we recommend is one we depend on. Most of them process your files on your device and never upload them.
The useful question about an AI system is not whether it is impressive but whether you can trust what it did. We design for that question.
01
Evaluated, not assumed
Models are measured on documents and data they have never seen, with precision and recall reported as numbers. When a result is illustrative we say so.
02
Private by design
Where a job can run on your device, it does. Where it can't, we collect only what the product needs and encrypt what is sensitive.
03
A person is accountable
Agents propose and build; people decide. Every release, every data model and every recommendation has a named human who stands behind it.
04
Secure from the first commit
Strict content security policies, reviewed dependencies, signed audit trails and independent review before anything reaches a customer.
Contact us
Bring us the decision, the document or the backlog.
Tell us what you are trying to build, automate or understand. A person reads every message and replies, usually within two working days.
Software and agentsProducts, internal tools, agent-run workflows
Document intelligenceExtraction, field detection, on-device processing
AnalyticsData platforms, forecasts, dashboards people use