Expansion and strategy teams
Evidence for every location bet.
Capability
Geospatial & Location Analytics
Decide where to build, serve, route and sell using the map, not the guess.
Forecast accuracy for new sitesDistance and fuel per deliveryService coverage of target populationTerritory workload balance
The service at a glance
The problem, our work, your result
- Business problem
Location decisions are made from habit, not evidence.
Where to open a branch, place a warehouse or route a fleet is answered with spreadsheets and opinions.
- What we do
We combine your data with maps, movement and demographic layers to answer where questions: site selection, catchment analysis, routing and risk mapping.
- What you receive
- Site selection models
- Catchment and coverage maps
- Route and network optimisation
- Geospatial dashboards
Who it is for
Built for the people who own the decision
Logistics leaders
Shorter routes, fuller vehicles.
CFO and finance
Capital spent where it returns.
Risk, compliance and security
Exposure mapped by geography.
The goal: an AI-ready organisation
Where this service moves you
Data readyThis service
Connected, clean, governed and allowed for AI use.
KPIs readyThis service
Agreed measures, one definition each, a named owner.
Organisation ready
Roles, decision rights and skills to adopt AI safely.
=AI that reaches production and creates value
Approach
How we work with you
- 01
Frame
Define the where question precisely.
- 02
Layer
Combine your data with map layers.
- 03
Model
Score and compare options.
- 04
Decide
Present ranked, mapped recommendations.
Engagement options
Start where you are
One question study
A site or network question answered.
Location platform
Ongoing geospatial analytics.
Network strategy
Full footprint design and optimisation.
Scope
What is in, what is not
Included
- Geospatial data assembly
- Analysis and modelling
- Map dashboards
- Recommendation reports
Handled separately
- Property negotiation
- Construction and fit-out
Bilytica frameworks behind this service
Our own methods, not a generic playbook
DFF
All Bilytica frameworksData Foundation Framework
The layers that turn scattered systems into data an AI system is allowed to use.
See the frameworkVALUEAI Value Framework
From use-case long list to booked benefit, with unit economics attached at every step.
See the frameworkIn short
What this actually is
Site selection, catchment and cannibalisation modelling, territory design, route optimisation, coverage and accessibility analysis, built on your own operational data plus mapping, mobility and demographic layers. Delivered as maps decision-makers can interrogate, not a one-off consulting deck.
Key points
What matters before you buy
- 01
Site selection stops being an argument
Catchment, competition, access and cannibalisation modelled openly, so the board debates assumptions instead of opinions.
- 02
Routing pays back fastest
Distance, time windows, vehicle constraints and real road conditions applied daily to the fleet you already run.
- 03
Coverage gaps become visible
Where a service, a branch or a network cell does not reach the population it is meant to serve.
- 04
Your data first, external layers second
Transactions, visits and assets carry more signal than any purchased demographic file.
Delivery
How we build it
Foundation check
Before any buildWe inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.
Narrow first release
First releaseOne workflow, one team, real traffic, measured against the baseline we captured before we started.
Controls and evaluation
Runs in parallelGuardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.
Scale and hand over
After sign-offAdditional workflows, sites or languages, then runbooks and training so your team can operate it without us.
Data foundation
What has to be true in your data first
Great AI cannot hide bad data. These are the conditions this capability depends on, we fix them as part of delivery, not after go-live.
- Geocoded transactions, sites or service events, the single biggest quality blocker.
- An agreed boundary and territory definition everyone uses.
- Licensed mapping, mobility or demographic layers where the question needs them.
- Historical performance by location for calibration.
Controls
Guardrails we put around it
Every action is logged and replayable
Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.
Data stays where your regulator requires
In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.
Accuracy is monitored, not assumed
A held-out evaluation set runs on every model or prompt change, with drift alerts and a documented rollback path when quality moves.
Location data is personal data
Individual movement traces are aggregated before analysis, and licensing terms for external mobility data are checked before it enters a model.
Fit
Systems it plugs into, and what it moves
Integrations
Google Maps PlatformEsri ArcGISQGIS / PostGISMapboxSnowflake / BigQuery geospatialTelematics and fleet systems
KPIs it moves
- • Forecast accuracy for new sites
- • Distance and fuel per delivery
- • Service coverage of target population
- • Territory workload balance
- • Cannibalisation of existing sites