AI-native web & mobile apps
Full product builds — interface, backend, data layer and deployment — where the AI is the product, not a bolt-on chat bubble in the corner.
02 For Founders, product leaders and innovation teams
AI Product Development — Web, Mobile and Agentic Products, Taken to Production
Most AI products die between the demo and the deadline. We build the unglamorous half — evaluation, guardrails, fallbacks, observability and cost control — so the thing you demo is the thing your customers can actually use on a Tuesday.
85+
AI agents running in production environments99%
Uptime across production deployments200K+
Conversation sessions on ZAP AI96%
Query resolution by the RIZ BI agentFigures from production deployments documented in our case studies.
The problem
The gap between a working demo and a working product
- The prototype was convincing. It is now four months later and nothing has shipped.
- Nobody can say whether the model got better or worse after the last change.
- Token spend scales linearly with users, and the unit economics stopped working at a thousand of them.
- The agent is confidently wrong often enough that support has quietly stopped trusting it.
- Your engineers are excellent, and none of them have taken an LLM system to production before.
What we build
AI Product Development, in practice
Agentic backends
Retrieval, tool use and multi-agent orchestration with the retry, fallback and escalation paths that keep an agent useful when a step fails.
Conversational learning products
Guidance and coaching experiences of the kind behind ZAP AI and Jelliemons — 200K+ conversation sessions and 3x engagement, across education and consumer gaming.
Embedded BI agents
Natural-language analytics inside your own product. Our RIZ agent resolves 96% of business queries without an analyst in the loop.
Data & cloud foundations
Warehouse, pipelines and event plumbing built once, properly — the layer that decides whether the AI on top is possible at all.
Evaluation & observability
Regression suites, tracing and cost dashboards from the first week, so quality and spend are measured rather than argued about.
How we work
Assess, architect, build, integrate, operate
The same five stages on every engagement. You see production increments from week six, not a reveal in month seven.
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01
Assess
A two-week diagnostic. We map the workflow, the data and the constraints, and come back with the intervention that pays for itself first — occasionally not the one you asked about.
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02
Architect
Solution design, data contracts, model and vendor selection, and a cost envelope you approve before anyone writes production code.
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03
Build
Production increments every two weeks with your team in the loop. No six-month silence ending in a reveal.
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04
Integrate
Connected to the systems you already run, then operated in parallel with the current process until the numbers justify the cutover.
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05
Operate
Monitoring, evaluation suites, retraining and optimisation — plus training for the team who will own it after we step back.
Built on
OpenAI
Anthropic
LangChain
React
Next.js
React Native
Python
BigQuery
Proof
Where this has already run
Each of these is a full case study with the architecture, the constraints and the numbers.
Questions we get asked
Before you book a call
Do you work alongside our in-house engineers?
Frequently, and it is usually the better outcome. We take the AI systems work and the production hardening, your team keeps domain ownership, and we hand over documented and tested rather than leaving a black box behind.
Can you take over a stalled build?
Yes. We start with a short technical audit of what exists, tell you plainly what is salvageable, and rebuild only the parts that are genuinely in the way.
Who owns the code and the models?
You do — repositories, prompts, evaluation sets and infrastructure definitions, all in your accounts from day one.
How do you keep inference costs sane?
Model routing by task, aggressive caching, distillation of hot paths onto smaller models, and a cost dashboard reviewed in the same meeting as the quality metrics.
Explore
The rest of the system
These pillars are built to work together — the CRM feeds the voice agent, the voice agent feeds the growth engine.
AI-First ERP & CRM
Custom operating systems for retail, logistics & real estate
Digitalization & Growth
SEO, GEO and AI marketing systems that compound
AI Voice & Chat Agents
Multilingual agents on the phone, the web and WhatsApp
AI Counselling & Upskilling
The HI Platform — fellowships, cohorts and pre-vetted hiring