Custom AI Solutions
Custom AI Solutions & AI Integration Services
When off-the-shelf AI tools don't fit your data, systems or requirements, we build custom AI software and integrate it into the applications your business already depends on.
Discuss your projectGeneric AI tools stop short of your real problem
Public AI assistants are useful, but they don't know your products, can't access your internal systems, and often can't be used with sensitive data. Point solutions solve one narrow task and add yet another login for your team.
The value of AI for most businesses comes from connecting it to their own data and workflows — and that requires engineering, not just a subscription.
AI built for your data, systems and constraints
We assess where AI can make a measurable difference, then design and build the solution — from a smart search over your documents to prediction models or AI features inside your existing software — with the security and deployment model you need.
What we deliver
- AI features integrated into existing web, mobile or internal applications
- Semantic search and question answering over company documents
- Machine learning models for classification, forecasting and scoring
- Computer vision and document understanding
- Secure deployment in your cloud, with access controls and logging
How it works
- Step 1
Assess
We review the business problem, available data and existing systems to confirm AI is the right tool.
- Step 2
Prove
A proof of concept on your real data shows what quality is achievable before larger investment.
- Step 3
Integrate
The model or LLM feature is connected to your applications through APIs, with user permissions respected.
- Step 4
Operate
Monitoring, evaluation and retraining or prompt updates keep quality high over time.
Business benefits
Fits how you work
AI appears inside the tools your team already uses, which drives adoption.
Your data stays under control
We design for your security, privacy and residency requirements, including private deployments.
Evidence before scale
Proofs of concept on real data reduce the risk of investing in an approach that doesn't work.
Maintainable engineering
Documented, tested code and clear evaluation metrics, so the solution can evolve.
Use cases
Knowledge search
Ask questions across manuals, contracts, tickets and wikis and get cited answers.
Predictive models
Demand forecasting, lead scoring or churn prediction from your historical data.
AI inside your product
Summaries, smart suggestions, auto-tagging or natural-language search for your users.
Document and image understanding
Read forms, IDs, receipts or product images and turn them into structured data.
Our process
Discovery & data review
Goals, success metrics, data access and constraints.
Proof of concept
A focused experiment on real data with an honest assessment of results.
Production build
Integration, security, testing and deployment.
Monitoring & improvement
Quality tracking, retraining and feature updates.
Read more about how we work.
Technologies we use
- Python
- PyTorch
- TensorFlow
- OpenAI API
- LangChain
- Vector databases
- Node.js
- Docker
Frequently asked questions
Do we need a lot of data to use AI?
Not always. Language-model features can work with relatively little company data by retrieving from your documents. Predictive machine learning usually needs a meaningful amount of historical data — we'll assess what you have before recommending an approach.
Can you integrate AI into our existing software?
Yes, that's most of our work. We integrate through your application's APIs or database, or build a separate service your systems call.
Can the solution run in our own cloud?
Yes. We can deploy into your AWS, Azure or Google Cloud account and use models that keep data within your environment where required.
How do you measure whether the AI works?
We agree evaluation criteria up front — accuracy on a test set, time saved, or user feedback — and measure against them during the proof of concept and after launch.
Related services
AI Consulting
Practical AI consulting from engineers who build: find high-value AI use cases, assess data and risks, and get a realistic roadmap and proof of concept.
AI SaaS Development
AI SaaS development from idea to launch: MVP scoping, multi-tenant architecture, LLM features, billing and scalable infrastructure for founders and startups.
AI Automation
AI automation services that take repetitive, judgement-based work off your team: document processing, email triage, support and reporting, in your own tools.
Have an AI idea for your business?
Describe the problem and the systems involved. We'll suggest a practical first step, often a small proof of concept.
Contact us