Generative AI development, production-ready.
We design and build generative AI applications that solve real enterprise problems — grounded in your governed data, integrated with your systems, and governed for safety, accuracy and cost from prototype to production.
GenAI that works on your data, not just demos.
Generative AI development turns large language and generative models into applications that draft, summarise, answer, classify and automate real work. RapidData builds GenAI grounded in your own knowledge through retrieval-augmented generation (RAG), so output is accurate and current rather than hallucinated.
We are model-agnostic: our LLM Mesh routes across commercial, open-source and private models so you use the best model for each task and avoid lock-in. Every GenAI application we ship is integrated with your systems and governed with evaluation, guardrails and audit.
From rapid prototype to hardened production deployment, we deliver GenAI with a clear business case, a named KPI, and capability transfer to your team.
GenAI Application Development
We build production GenAI applications — copilots, assistants, document intelligence, content generation and classification — grounded in your data and wired into your workflows.
RAG applications
Ground GenAI in your governed documents and data.
Copilots & assistants
Domain copilots embedded in your tools and processes.
Document intelligence
Extraction, summarisation and classification at scale.
LLM integration
Model-agnostic integration via an LLM Mesh.
Evaluation, Safety & Governance
GenAI needs guardrails. We add evaluation, safety filters, human-in-the-loop and audit so output stays accurate, safe and compliant.
Evaluation
Continuous accuracy, safety and cost evaluation.
Guardrails
Policy-as-code constraints on what models can do.
Human-in-the-loop
Approval checkpoints on high-risk output.
Audit & observability
Full logging of prompts, outputs and decisions.
Deploy & Operate
Deploy on your infrastructure and run with MLOps discipline so GenAI stays reliable and cost-effective.
Deploy anywhere
Cloud, on-premise or sovereign deployment.
MLOps
Monitor drift, latency, accuracy and cost.
Cost control
Routing and caching to manage token spend.
Managed run
Operate and improve under named SLAs.
Related capabilities & platforms.
Frequently asked questions
What is generative AI development? +
Building applications powered by large language and generative models — grounded in your governed data via RAG — to draft, summarise, answer, classify and automate work.
How do you prevent hallucinations? +
We ground models in your own governed knowledge via retrieval-augmented generation (RAG), add evaluation and guardrails, and insert human-in-the-loop checkpoints on high-risk output.
Which LLMs do you use? +
We are model-agnostic and route across commercial, open-source and private models via an LLM Mesh, choosing the best model per task to avoid lock-in.
Can GenAI integrate with our systems? +
Yes. We integrate GenAI with your ERP, CRM, data platforms, ticketing and custom systems.
How fast can we get a GenAI prototype? +
A working prototype is typically delivered in weeks, with a clear path to a governed production deployment.
Is it secure and compliant? +
Yes. We deploy on your infrastructure with RBAC, encryption, data-residency options and full audit logging.
Build your first GenAI application.
Talk to our GenAI team about a high-value use case and a fast, governed path to production.