AI Products & LLM Development
Custom AI products, chatbots, RAG systems and agents that ship to production.
We design and engineer production-grade AI products — from LLM-powered chatbots and copilots to retrieval-augmented (RAG) search, document intelligence, and autonomous agents. Every project is grounded in evaluation, safety, and a clear ROI path, not demos.
Benefits you can measure.
Most AI projects die between the impressive prototype and a reliable product. We specialise in the boring parts that make AI actually work in production — evaluation, guardrails, latency budgets, cost controls, and human-in-the-loop workflows.
Model-agnostic architecture
OpenAI, Anthropic, Google, Meta Llama, Mistral or self-hosted — we pick per use case and never lock you in.
RAG done right
Chunking, embeddings, hybrid search, reranking and citation UX so answers are grounded, verifiable and trustworthy.
Evaluated, not vibes
Golden datasets, LLM-as-judge scoring and regression suites so quality is measurable and improves release over release.
Safety, PII and cost controls
Prompt-injection defences, PII redaction, per-tenant budgets, rate limiting and audit logs from day one.
What you'll receive
- Use-case discovery and success metric definition
- Data pipeline, embeddings and vector store setup
- LLM orchestration (prompts, tools, agents) with guardrails
- Evaluation harness and quality dashboard
- Production API, admin console and monitoring
- Handover, runbooks and prompt/model-update workflow
How we work
- 1Week 1 — Discovery, data audit and eval design
- 2Week 2–4 — Prototype, prompt engineering and RAG build
- 3Week 4–7 — Guardrails, agents, tool integrations
- 4Week 7–8 — Load testing, cost tuning and launch
What this looks like in practice.
Built a Bangla-first conversational AI product from data collection through fine-tuning, evaluation and production launch.
Deshi GPT needed a large-language-model experience that felt native to Bangla speakers — a market underserved by global models. We designed the retrieval pipeline, curated evaluation sets, fine-tuned on domain data and shipped a production API and web app with strict safety filters, per-user budgets and telemetry.
What clients say about this service.
"They took our AI idea from a Colab notebook to a real product with evaluation, safety and monitoring. It just works."
Questions about AI Products & LLM Development.
Which LLM providers do you work with?+
All major hosted providers (OpenAI, Anthropic, Google, Cohere) and open-source models (Llama, Mistral, Qwen) via self-hosting or vLLM. We recommend per use case based on quality, latency, cost and data-residency needs.
Can you fine-tune models on our data?+
Yes — supervised fine-tuning, LoRA/QLoRA, and preference tuning (DPO) on open models, plus provider-hosted fine-tuning where it's a better fit than RAG.
How do you keep our data private?+
We default to zero-retention provider settings, self-hosted options for sensitive data, PII redaction in the pipeline, and full audit logs. Your data is never used to train shared models.
How do you measure AI quality?+
Every project ships with a golden evaluation set, automated LLM-as-judge scoring, regression tests in CI, and a quality dashboard so quality is measurable — not anecdotal.
Ready to talk about ai products & llm development?
Send a few details and a senior team member will reply within one business day with concrete next steps — no automated funnels.
Other ways we can help.
Web Design & Development
Bespoke websites and web apps engineered for performance, accessibility and scale.
Mobile Apps Development
Native and cross-platform iOS and Android apps with production-grade architecture.
B2B & B2C SaaS Software
End-to-end SaaS platforms — auth, billing, dashboards and APIs your team can extend.