Loading
Loading
We design, build and deploy AI-powered products and automation systems — LLM integrations, RAG pipelines, AI agents and custom ML workflows — that create measurable business value, not demos.
What Is AI Product & Automation Development?
AI product and automation development is the engineering work required to turn a promising AI capability into something that runs reliably in your product, touches real business data, and produces outputs your team can act on — every time, not just in a controlled demo.
RAG (retrieval-augmented generation) means connecting a language model to your own documents, databases, or APIs so it answers questions grounded in your actual data rather than its training set. AI agents are autonomous systems that can plan, call tools, and take actions across multiple steps — booking, classifying, routing, drafting — without a human driving every step. Most AI proof-of-concepts demonstrate these capabilities in isolation. The hard part is the engineering: integrating them into your existing systems, making them robust under real user behaviour, and instrumenting them so you know when they go wrong.
Most AI projects fail not because the underlying model is wrong, but because the integration work is underestimated. Cyberbeak approaches AI development the same way we approach any production system: with proper architecture, observability, testing, and a clear definition of what success looks like in business terms — whether that is working with OpenAI, Anthropic, or an open-source model appropriate for your data sovereignty requirements.
“The demo was impressive. Then we tried to connect it to our actual data and it fell apart.”
Most AI proof-of-concepts never reach production because the engineering work required to integrate them into real systems — authentication, data pipelines, error handling, latency budgets — is severely underestimated.
Off-the-shelf AI tools add surface-level features but can't model your proprietary business logic or data, which means outputs are generic, often wrong, and require manual review before anyone acts on them.
Internal teams may have ML knowledge but not the product engineering depth to ship a production system — the gap between a working notebook and a deployed, monitored, maintained AI feature is larger than it looks.
AI automation that isn't grounded in real business data produces outputs no one trusts or acts on — hallucinations and confident-but-wrong answers are a deployment problem, not a model problem.
What We Build
From LLM integrations to autonomous agents — built for production, owned by you.
We integrate large language models from OpenAI, Anthropic, and open-source providers directly into your product or workflow. Where a general model falls short, we fine-tune on your domain data so outputs are accurate, on-brand, and actionable.
Retrieval-augmented generation systems that ground LLM outputs in your proprietary documents, databases, and real-time data sources. We design the chunking strategy, embedding pipeline, vector search, and reranking layer — not just the chatbot front-end.
Autonomous agents that plan, tool-call, and act across your business systems — from data extraction and classification to multi-step approval workflows. We build with guardrails, observability, and human-in-the-loop escalation built in from the start.
Embedding AI capabilities — smart search, content generation, anomaly detection, recommendation engines — directly into your existing product so they feel native, not tacked on. We handle the backend model serving and the UX integration together.
End-to-end machine learning pipelines covering data ingestion, feature engineering, model training, evaluation, and deployment. We work with your data science team or lead the entire pipeline build, depending on your internal capacity.
Production AI systems degrade without monitoring. We instrument your models with latency tracking, output quality metrics, drift detection, and cost alerting — so you know when to retrain, swap models, or intervene before users notice.
Decision Framework
Typical integration to production
Clutch rating across all engagements
AI and software products shipped
Delivery across UK, UAE, US, APAC
Stack
FAQ
Tell us what you need AI to do. We'll tell you the right approach, the model fit, and what it'll take to get to production.
Start Your Project