We design and develop AI solutions that feel natural to users and work reliably in production. From LLM integrations to RAG knowledge assistants and agentic workflows, we help you ship AI features that improve speed, reduce manual work, and unlock smarter operations. Every solution is built on a decade of fullstack and UI/UX experience, so the AI feels like a natural part of your product, not a bolt-on experiment.
AI is evolving rapidly, but businesses still need solutions that are practical, secure, and measurable. At Amilek, we focus on real use cases: support automation, document intelligence with citations, workflow automation using agents, and LLM-powered features inside SaaS platforms. We combine product UX thinking with clean engineering, so your AI delivers consistent, trustworthy results in everyday use.

We design AI experiences that are easy to use, fast, and clear. Good UX is the foundation, not an afterthought.
We use structured outputs, validation, and fallback flows, so results stay consistent and dependable in real use.
We integrate AI safely with controlled access, logging, and performance monitoring built in from the start.
We add admin controls, feedback loops, and workflows that match how your team actually operates day to day.
We understand your users, data sources, workflows, and success metrics before writing a single line of code.
We map the experience and define exactly how AI fits into your product journey.
We implement the AI layer, APIs, security, and the tool integrations your product needs.
We test with real scenarios, tune the quality, and deploy with monitoring in place.

We build AI solutions using modern, proven stacks including OpenAI, Claude, and Gemini, orchestration frameworks and custom workflows, and vector databases such as pgvector, Qdrant, and Pinecone. Our backends run on scalable technologies like Node.js, Next.js, and FastAPI. We also integrate with the business tools you already use, including Slack, ClickUp, CRMs, and internal APIs, to deliver production-ready AI workflows.

A standard chatbot answers from general knowledge or a fixed script. A RAG assistant reads your own documents, data, and files before answering, so it gives accurate, up-to-date responses about your specific business, complete with sources. In short, a chatbot talks; a RAG assistant answers from your real information.
No. AI handles the repetitive, high-volume questions so your team can focus on the complex cases that need a human touch. It reduces workload and speeds up responses, but your people stay in control of the conversations that matter most.
We ground answers in your own data using RAG, apply structured outputs and validation, and add fallback flows so the AI says "I don't know" instead of guessing. For sensitive cases, we add source citations and human review, so you can trust what the system tells your users.
Yes. We integrate with popular tools like Slack, ClickUp, and major CRMs, as well as your internal systems through APIs and webhooks. If your tool has a connection method, we can usually work with it.
A clear idea of the problem you want to solve, access to the relevant data or tools, and a point of contact on your side. From there we handle discovery, design, and delivery. The clearer your goal, the faster we can build the right solution.