Accorda Solutions
Deploy AI That Actually Works in Your Business.
LLM strategy, RAG systems, and production AI copilots we cut through the noise and build Generative AI that your team can use, trust, and scale.
What we do
Every business is being told they need to adopt AI. Most are running pilots that never reach production, experimenting with tools that do not integrate with their data, or building on foundations that will not hold up under real usage. The gap between an impressive demo and a system that runs reliably in your business is where most GenAI projects fail.
We work at that gap. We help organisations identify where Generative AI will genuinely move the needle and where it will waste budget. Then we build: retrieval-augmented generation (RAG) systems grounded in your own data, copilots that fit naturally into existing workflows, AI agents that automate multi-step tasks, and evaluation pipelines that tell you whether your system is actually performing.
Our approach is pragmatic. We use the best available models OpenAI, Anthropic Claude, open-source alternatives matched to your specific requirements around latency, cost, privacy, and capability. We do not lock you into a single vendor and we do not build black boxes. Every system we ship comes with observability, evaluation tooling, and a team that understands what it is doing.
What you get
Working AI copilots and assistants
Internal tools that help your team work faster: document summarisation, knowledge retrieval, code assistance, and decision support grounded in your data, not generic internet training.
Document and knowledge intelligence
RAG systems that let your team query years of internal documents, contracts, or support tickets with natural language and get accurate, cited answers.
Automated workflows and agents
AI agents that handle multi-step tasks: research, classification, routing, drafting, and more reducing the manual work that slows your team down.
AI strategy clarity
A clear picture of where GenAI fits in your organisation, what to build first, what to buy, and what to avoid so you invest in the right places from the start.
How we work
A structured approach that moves fast without skipping the steps that matter.
- 01
Use case identification
We map your workflows and identify where LLMs will create genuine value versus where they add complexity without return. We prioritise ruthlessly.
- 02
Proof of concept
We build a working prototype fast often in one to two weeks so you can validate the approach with real users before committing to a full build.
- 03
Evaluation and reliability engineering
We build evaluation pipelines that measure accuracy, hallucination rates, and task success because shipping a GenAI system without evaluation infrastructure is shipping blind.
- 04
Production build
We engineer the full system: retrieval pipelines, prompt architecture, API integration, authentication, and the infrastructure to serve it reliably under real load.
- 05
Monitoring and iteration
We instrument your system for ongoing performance tracking, set up feedback loops from real users, and make sure the system improves over time not just at launch.
Common questions
Ready to get started?
Tell us about your situation. We will respond within one business day.
Start the conversation →