Services
AI development & automation
Custom AI development that puts your data to work: generative AI and LLM applications, RAG search grounded in your own sources, and AI agents that complete defined tasks. We build evaluations, human review, and cost controls into the system from the beginning.
Start with a task that matters
A useful AI project starts with a workflow, a responsible owner, and a measurable outcome. We map the work, examine the available data, and compare an AI approach with simpler automation before recommending a build.
- Internal knowledge assistants with source citations
- Document extraction, classification, and review, with machine learning and LLMs
- Customer support chatbots and assistants with escalation to people
- AI agents with explicit permissions and approval steps
Prove quality before expanding scope
We create a representative evaluation set with your team. Accuracy, failure modes, latency, and cost become reviewable measures. Retrieval systems are tested for missing evidence; actions are constrained by permissions and validation.
Build for the environment you operate in
Your systems need to handle incomplete inputs, changing models, and upstream outages. We design fallbacks, record useful diagnostics, and separate model behavior from business rules. Sensitive data and third-party processing are considered during architecture, before implementation.
What you receive
An agreed scope, working software, evaluation results, deployment configuration, and operating documentation. We plan support or handover around the capabilities of your team.
- Model and provider selection backed by evaluations
- Integration with your existing applications and data
- Monitoring for quality, latency, and spend
- Documented limits and a practical improvement backlog
Common questions
How much does AI development cost?
Scoping has a fixed fee. Once the scope is clear, you choose a fixed-price build against an agreed specification or a monthly rate for an embedded team. We quote after understanding the work, your data, and the quality you need.
How long does it take to build an AI application?
About a week to scope, then a two-to-three-week prototype aimed at the hardest part of the problem. Most projects reach production eight to sixteen weeks from kickoff, with working software to review every two weeks.
Which AI models and providers do you use?
Whichever performs best on your tasks. We evaluate models against your quality requirements and budget and keep the model layer replaceable, so you are never tied to one provider and can switch when the evidence says so.
Who owns the AI system you build?
You do, from day one. Code, prompts, evaluation sets, and infrastructure definitions live in your accounts and repositories, and we document the work for a handover or ongoing support.