Featured case study
Aires de Río / Habitat Prime
SvelteKit marketing site with map search, floor plans, gated downloads, and lead admin.
Production web apps and data interfaces for teams who care about what's under the hood.
Software engineering for data-rich, interactive systems.
Problems clients hire Infomerx to solve
- Build or modernize a production web app (SvelteKit/TypeScript by default; React on request).
- Turn dense datasets into usable dashboards and maps.
- Rescue or refactor fragile internal tools.
- Prototype technical products involving 3D, ML/Python services, or complex browser UX.
Currently accepting new engagements; replies usually within two business days.
Infomerx builds production-grade web applications, data visualization platforms, technical prototypes, and software systems where clarity, performance, and engineering depth matter.
systems map clarity · performance · delivery
1
Product interface
SvelteKit · TypeScript · UX architecture
2
Data layer
SQL & NoSQL · APIs · ingestion · validation
3
Visualization
Charts · maps · 3D · interaction
4
Automation
Python services · ML integration · workflows
-
~3
leads per day average
during active campaign window
-
~US$1
per lead during campaign
ad spend efficiency at launch
-
400+
daily visitors during peak
campaign traffic to the site
-
Live
production launch
deployed with ops and admin tooling
Clear about delivery
We focus on systems that are useful, maintainable, and built for the long run. No hype, no vaporware — just shipped work and honest context.
Evidence in shipped work
Case studies name delivery context (LLC, subcontract, programme, or in-house), link public references where they exist, and separate client-facing launches from pre-release products—so you can evaluate claims against something concrete.
Heat Pump Market Tracker
- Open source
- Programme work
Open-source geographic dashboard for UK heat pump installs—map–chart cross-linking, filters, a11y, backend pipelines.
Color Lab
- Open source
- Live
- Independent R&D
MIT open-source live public beta: WebGL2 gamut solids, observer-aware colorimetry, per-list ramp pipelines, and shareable documents.
Capabilities
Senior engineering without the ceremony.
Production web applications
SvelteKit, TypeScript, backend services, admin systems, dashboards, and client-facing platforms built for maintainability.
Data visualization systems
Accessible, high-density interfaces for charts, maps, filters, metrics, and exploratory analysis.
Geospatial interfaces
Map-driven products, spatial dashboards, public-sector tooling, and location-aware UX.
AI & technical prototypes
Practical integration of Python services, ML workflows, automation, experimental engineering tools, and browser-native domain-heavy UIs (e.g. computational 3D or analysis loops).
How engagements run
Discovery
Align on goals, constraints, and evidence of success before committing to a stack or schedule.
Architecture
Choose patterns, boundaries, and milestones that stay shippable—no surprise “big bang” reveal.
Delivery
Incremental releases with review, automation, and documentation that survives handoff.
Hardening
Operational basics—monitoring hooks, runbooks, and support scope—are part of done.
Technical depth without theatrics
Most products sit between a browser surface, a data layer, and services that do the slow or specialized work. The diagram is schematic: your deployment will differ; the discipline does not.
Interface SvelteKit · a11y · maps & charts
Application APIs · validation · auth boundaries
Data Elasticsearch · PostgreSQL · MongoDB · S3 · Redis · SQLite · APIs · validation
Automation Python · jobs · ML when it earns its place
Case studies show how these layers showed up on real projects. Typical tooling on the stack page.
Common starting shapes
Examples of how a first milestone is often bounded. Detail and deliverables stay on Capabilities.
Vertical slice spike
Two to three weeks: discovery plus a narrow vertical slice and a clear go/no-go for the full build.
Map–list coherence slice
Two weeks: synced filters, one representative layer stack, and a short operator checklist for data prep and deployment.
Model-backed operator flow
One to two weeks: one model-backed flow with failure semantics, logging, and human-in-the-loop guardrails.
Have a complex SvelteKit, data, map, or internal-tool problem?
Send the current state, the desired state, and the first milestone you need. Replies include clarifying questions, a rough sense of fit, and a proposed first milestone.