We build
intelligence
into software.
Axiom Analytics designs data platforms, AI systems and digital products that turn complex information into clear decisions and practical workflows.
From raw observations
to one clear decision.
We engineer pipelines that ingest, validate, normalise, enrich and model high-volume data — then deliver it through practical dashboards, APIs and decision workflows.
See data in its geographic context.
Geospatial indexing, spatial joins, catchment analysis, point-of-interest intelligence and location scoring turn latitude/longitude data into a comparable analytical layer.
Combine movement, place and profile.
Bring together mobility observations, geography, population, household context, consumer expenditure, socio-economic indicators and other reference data using consistent spatial keys.
Statistical modelling
Weighting, calibration, anomaly treatment, temporal adjustment and confidence-aware interpretation.
Segmentation & ML
Clustering, classification, similarity and propensity approaches for audience and consumer profiling.
Data engineering
Recurring ingestion, validation, de-duplication, partitioning and batch pipelines built for production operations.
Decision interfaces
Make complex analytics usable through clean dashboards, maps, reports and application APIs.
Software should make complexity disappear.
We design full-stack web applications that combine workflow, analytics and AI in one coherent product.
From project administration and data capture to model orchestration, review, reporting and role-based workflows, we build the application around the work people actually need to complete.
From pixels
to evidence.
See. Track. Measure. Review.
Object detection
Custom visual detection for domain-specific objects, logos, products and classes — with project-specific training and validation.
Person tracking
Convert repeated frame-level detections into continuous tracks for footfall, dwell and behaviour measurement.
Visual attention
Browser-camera gaze estimation, calibration, timestamped coordinates, heatmaps and sequential attention analysis.
Human-in-the-loop
Annotation, validation and review workflows keep people in control when model output needs correction or confirmation.
Built for problems that do not fit neatly into a spreadsheet.
Footfall & dwell
Transform long-duration CCTV footage into visit, dwell and defined behaviour datasets.
Brand & object detection
Detect many small visual targets in cluttered scenes, backed by annotation and quality-control workflows.
Gaze & heatmaps
Measure where people look, attention concentration and the sequence in which visual elements are noticed.
Model → metric
Turn AI detections into structured, timestamped, business-ready measures rather than stopping at model output.
Today’s assignments
Built for the field.
Ready for the real world.
Mobile and PWA experiences for distributed teams, inspections, audits, evidence capture and operational workflows.
Trusted capture
Location, time and device context can be enforced at the point of data collection.
Offline-first workflows
Keep work moving in low-connectivity conditions and synchronise when the network returns.
Auditability
Assignments, evidence, roles, timestamps and status changes create a defensible operational trail.
Learning systems that explain, practise and remember.
We apply product design, structured content, assessment workflows and generative AI to create focused learning experiences — designed around mastery, not screen time.
Visit Solver7Solver7
Problem first.
Technology second.
We start with the decision, workflow or measurement problem. Then we choose the data, architecture and AI pattern that can solve it reliably.
Discover & frame
Define the user, workflow, data, constraints and measurable outcome before choosing a model.
Design & engineer
Build clean service boundaries, data flows, APIs, controls and user experiences around the real task.
Build & validate
Test data quality, model behaviour, application logic, edge cases and human-review points.
Deploy
Move from prototype to production with versioned services, controlled releases and rollback-aware deployment.
Observe
Monitor data, jobs, errors, usage and service health so the system remains understandable in production.
Improve
Use production evidence to refine models, rules, interfaces and workflow performance over time.
Practical technology. Chosen for the job.
We use open, proven components and fit the stack to the workload — data processing, spatial computation, model inference, application delivery or AI-assisted interaction.
The architecture follows the problem — not a fixed technology checklist.
Useful is the standard.
A good system is not defined by how much technology it contains. It is defined by whether people can trust it, use it and make better decisions with it.
Outcome-led
Start with the business, research or operational outcome — not the technology trend.
Evidence-led
Tie claims to data, validation, measured behaviour and transparent analytical rules.
Human accountable
Keep review and correction paths where model uncertainty or business risk requires them.
Production-minded
Design for APIs, operations, logging, access controls, repeatability and maintainability from the start.
Let’s build something useful.
Talk to Axiom Analytics about data platforms, AI systems, web applications, mobile workflows, analytics products or education technology.
[email protected]