01Frame
Name the decision before opening the dataset.
We establish what someone needs to decide, what they know today and what prevents them from acting.
A decision worth solving for.DATA, AI & LOCATION INTELLIGENCE
Data that
ends in a
decision.
From paper records to live maps, we engineer the data and AI systems behind your next decision. We start by finding what is stopping it.
NEW DELHI / OUR BASEView case ↗
A FEW PLACES OUR WORK TAKES US
Representative regions, not exact client locations.
06years
Working since 2020
478+
[CONFIRM: projects delivered]
30+ countries
[CONFIRM: coverage definition]
50+ team members
Engineering, analytics and GIS
01 / HOW WE THINK
The problem sets the direction.
Data led.
Every recommendation comes with evidence you can examine.
Solution driven.
The problem determines what we build.
Complex
problem solving.
Paper records and conflicting systems are familiar starting points.
Progressive.
We build systems your team can keep improving.
02 / WHAT WE DO
Six services. Shaped around your problem.Whatever sits between
the data and the decision.
Some answers sit in paper records. Others depend on connecting a workflow to the map.
01
Data Engineering & Automation
Connect scattered records and automate the re-keying, checks and handoffs around them.
02AI Engineering
Build AI around your documents and operating rules, on your servers or fully offline where required.
03Location Intelligence
Put land, assets and demand on the same map to decide where to act.
04Analytics
Make forecasts and dashboards that answer a specific business question.
05Migration & Modernisation
Move legacy systems and paper records onto usable platforms while preserving their history.
06Managed Services
Keep the systems we build monitored, maintained and improving.
03 / THE WHOLE CHAIN
One example: mineral rights acquisitionHow data becomes a decision.
01 / RAW SOURCES
The information.
Paper · Spreadsheets · ERPs
Sensors · Satellite · Maps
02 / CONNECTED
A usable record.
Extract · Reconcile · Link
03 / DELIVERED
In the workflow.
Apps · APIs · Assistants
04 / SEEN
In context.
Dashboards · Maps
04 / THE FLODATA METHOD
Diagnosis before prescription.Walk the problem.
Then build.
No solution in the first meeting. We need to understand what the work actually demands.
Data Readiness Check02Walk
The brief is a starting point. The work tells us more.
We inspect actual records and follow the workflow with the people responsible for it. The diagnostic exposes missing information and practical constraints.
[CONFIRM: paid diagnostic]03Shape
Build only what the decision needs.
We recommend an approach that fits the problem, including reusing existing systems or reducing the scope.
A scope that earns its place.04Build
Choose the tools after the problem is understood.
We engineer the required data flows and interfaces. Bespoke development runs through every service.
The engineering follows the evidence.05Stay
Keep the system useful as the work changes.
We monitor what is running and extend it as operational needs develop. Support commitments are agreed explicitly.
[CONFIRM: support hours and response commitment]01 / 05
05 / SELECTED WORK
View all workThe work is the proof.
See how a tract map or a paper archive
becomes a place to work.
FLODATA / ACQUISITION WORKSPACESCHEMATIC
[ASSET NEEDED: 16:10 map workspace with a tract selected]
CASE/01
From tract to owner to offer.
One acquisition workspace, with outreach restrictions enforced by the system.
Under the hood
Leaflet · OpenStreetMap · [CONFIRM: remaining stack]
FLODATA / GROUND OPERATIONSSCHEMATIC
[ASSET NEEDED: 16:10 live operations dashboard]
CASE/02
Airport ground operations, on a live map
Vehicle positions and mapped incidents in one operational view.
Under the hood
[CONFIRM: stack]
FLODATA / CONNECTED PRODUCTSSCHEMATIC
[ASSET NEEDED: 16:10 connected product views using demo data]
CASE/03
A connected system for personal injury claims
Connected products support report discovery, clinic collections and patient retention.
Under the hood
AWS · Python · Flask · FastAPI · PostgreSQL · React · Gunicorn · Nginx · GitHub Actions
FLODATA / DOCUMENT INTELLIGENCESCHEMATIC
[ASSET NEEDED: 16:10 record search and document classification with dummy data]
CASE/04
Four decades of HR paper, made searchable
1,527 active and 178 inactive records structured for search and export.
Under the hood
OCR · Vision-language models · [CONFIRM: remaining stack]
FLODATA / LOCATION & DATASCHEMATIC
[ASSET NEEDED: 16:10 anonymised market clusters and entry sequence]
CASE/05
Choosing the next markets as a network
Adjacent market clusters and an order of entry grounded in the existing network.
Under the hood
[CONFIRM: stack]
06 / HOW WE START
Start with what is getting in the way.A problem is
enough to begin.
- 01
Describe the decision.
Tell us what is going wrong and where the information sits today.
- 02
Walk the problem.
We examine the records and speak with the people doing the work.
[CONFIRM: paid diagnostic] - 03
Agree the work.
We define what to build and how it will be supported.
A GOOD PLACE TO START