AI Solutions & AI Agent Development
Put AI to work where it creates real business value.
What you get
- AI opportunity assessment across your workflows
- Working proof of concept on your real data
- Production agent or automation with guardrails
- Evaluation suite and accuracy benchmarks
- Human-in-the-loop review interface
- Monitoring, logging and cost controls
- Team enablement and documentation
What we build in ai solutions.
AI agents
Agents that carry out real multi-step work inside your systems — triaging requests, preparing records, chasing missing information — with a human approving anything consequential.
Customer support automation
Assistants that answer from your own documentation and order data, resolve the routine majority, and hand over to a person with full context when they cannot.
Document intelligence
Extracting structured data from invoices, prescriptions, purchase orders, lab reports and contracts, then pushing it straight into the system that needs it.
AI knowledge assistants
Retrieval-augmented search across your policies, manuals and historical records, so staff get a sourced answer in seconds instead of asking a colleague.
Workflow automation
Removing the copy-paste between systems: routing, classification, summarisation and data entry handled automatically, with exceptions escalated.
Internal AI assistants
Private assistants grounded in your own data for sales, operations and finance teams, deployed so your data never becomes someone else's training set.
Business intelligence
Natural-language reporting over your operational data, so managers can ask a question directly rather than queue for a report.
LLM integration into existing products
Adding drafting, summarising, classification or search to software you already own, behind a proper evaluation and cost model.
What you should expect from this work.
Hours back, measured
We baseline how long a workflow takes before we touch it, then measure the same thing after. If the numbers do not move, it is not finished.
Accuracy you can audit
Every AI output is traceable to its source, with evaluation sets, confidence thresholds and a defined path for when the model is unsure.
Costs that stay predictable
Model choice, caching and routing are designed around your usage, so the bill scales with value rather than surprising you at month end.
What we typically build this with.
- Models
- Claude
- OpenAI
- Open-weight models
- Fine-tuning
- Patterns
- RAG
- Agentic workflows
- Tool use
- Evaluations
- Data
- Vector databases
- PostgreSQL + pgvector
- Embeddings
- Orchestration
- Model Context Protocol
- Queues & workers
- Webhooks
From idea to impact
- 01
Discover
Understand your business, users, goals and constraints.
- 02
Plan
Define the solution, architecture, roadmap and priorities.
- 03
Build
Design and develop using modern, scalable technologies.
- 04
Launch
Test, deploy, monitor and optimise.
- 05
Grow
Keep improving the product as your business evolves.
However we engage
- One point of contact who knows your project, not a rotating account manager
- Weekly progress you can see, in working software rather than status decks
- Fixed scope per phase, with changes priced before they are started
- Your code, your data and your accounts — handed over in full at any point
AI Solutions questions.
Can you integrate AI into a business we already run on other software?
Almost always, yes. AI usually sits alongside your existing systems rather than replacing them — reading from your database, calling your APIs, writing results back. What matters is whether the data it needs is accessible and reasonably clean. We check that first, because it is the most common reason AI projects stall.
How do we know where to start with AI?
We run a short assessment across your workflows and score each one on volume, time cost, error rate and how well-defined the task is. That produces a ranked shortlist. The first project should be something narrow enough to ship in weeks and visible enough that the result is obvious.
What happens to our data?
Your data stays yours. We use enterprise API tiers that exclude your inputs from model training, and for sensitive workloads we can run open-weight models in your own environment. Data handling, retention and access are agreed in writing before any integration is built.
What if the AI gets something wrong?
We design for that from the start rather than hoping it does not happen. Outputs cite their sources, confidence thresholds route uncertain cases to a person, and anything with financial, legal or clinical consequence requires human approval. You get logs of every decision the system made.
Ready to talk about ai solutions?
Tell us what you are trying to achieve. We will help you figure out the best way forward — and tell you honestly if we are not the right fit.
Prefer email? hello@novista.io