[02.1]
Cross-platform apps
iOS, Android and desktop apps with on-device and cloud AI features.
Service [02]
AI Custom Application Development
When off-the-shelf AI tools don't fit, we build the application that does — end-to-end, from model to interface.
Problem and approach
The problem
Generic AI tools can't see your proprietary data, don't match your workflow, and often can't meet your security or data-residency rules..
Generic AI tools can't see your proprietary data, don't match your workflow, and often can't meet your security or data-residency rules.
Our approach
Production-ready from day one.
We build custom applications around private or fine-tuned models, deploy them where your data must live, and design interfaces your team will actually adopt.
Capabilities
What we deliver.
Modular capabilities we combine into one coherent system for your use case.
[02.2]
Document intelligence
Extract, classify and validate data from invoices, contracts, forms and scans.
[02.3]
Computer vision
Detection, inspection and OCR pipelines for images and video streams.
[02.4]
Fine-tuning & distillation
Domain-tuned small models that beat general models on your task — at a fraction of the cost.
[02.5]
Private deployment
VPC, on-prem or air-gapped deployments with open-weight models.
[02.6]
Analytics & forecasting
Predictive models and AI-generated insights surfaced in custom dashboards.
Use cases
Where it pays off.
Examples of what this service can do for your business.
Example use case
Claims processing app
A mobile + web app that reads claim documents and photos, flags fraud signals and pre-fills adjudication.
Discuss a similar buildExample use case
Field inspection AI
Offline-first tablet app with on-device vision to detect equipment defects on site.
Discuss a similar buildExample use case
Private legal assistant
A contract review app running open-weight models inside the firm's own VPC.
Discuss a similar buildArchitecture
How it fits together.
A typical reference design — adapted to your cloud, data and security model.
How we build
From idea to production in 5 moves.
A fixed-scope, evidence-first process. You see working software every week — and real numbers before you commit to the full build.
1–2 weeks
Discover
We audit workflows, data and systems, then rank AI opportunities by ROI and feasibility.
2 weeks
Prototype
A working prototype on your real data, with evals that prove quality before we commit to a build.
6–12 weeks
Build
Weekly sprints shipping production code to your repos, with demos every Friday.
1–2 weeks
Deploy
Staged rollout with monitoring, guardrails, cost controls and team training.
Ongoing
Optimize
We measure outcomes, tune prompts and models, cut cost and expand to the next use case.
FAQ
Common questions.
Can the AI run fully on our infrastructure?
Yes. We deploy open-weight models (Llama, Mistral, Qwen) inside your VPC or on-prem, with no data leaving your environment.
Do we need to fine-tune a model?
Often not. We start with prompting and retrieval, and only fine-tune when evals show a clear quality or cost win.
Do you build mobile apps too?
Yes — React Native, Flutter or native Swift/Kotlin, depending on performance and on-device AI needs.
How long does a custom build take?
A production MVP typically takes 8–14 weeks, preceded by a 2-week discovery and prototype phase.
Explore
Other services.
AI Web Application Development
Production-grade web apps with LLM features built in — copilots, semantic search, generative workflows — shipped on a modern, scalable stack.
AI Agent Development
Autonomous and human-in-the-loop agents that plan, use tools and complete multi-step work across your systems — safely and observably.
Automation
Intelligent workflow automation that connects your apps, removes manual busywork and scales operations without scaling headcount.
[ Next step ]
Ready to scope your custom ai apps project?
Book a 30-minute strategy call. We'll map your highest-ROI AI opportunities and tell you honestly what's worth building.