LLM Integration
Plug large language models into your product. Prompt engineering, response parsing, streaming, caching — production-grade, not a wrapper.
AI That Ships.
Not AI That Demos.
Anyone can wrap an API and call it AI. We build production systems — deployed, monitored, and solving real problems. Not a science project. An engineering outcome.
Most AI Projects Never Leave the Lab
87% of AI projects never make it to production. Not because the tech doesn't work — because the engineering isn't there.
The gap between a notebook demo and a production system is enormous. Model selection, prompt engineering, latency optimization, error handling, cost management, monitoring — that's where most teams stall.
We don't. We're an AI-native team that builds production systems, not research experiments. If you've been burned by vendors who demo well but can't ship, you're in the right place.
AI That Works in the Real World
AI Agents
Autonomous agents that reason, plan, and execute. Tool use, memory, multi-step workflows. The kind of AI that actually gets work done.
Chatbots & Assistants
Customer-facing or internal. Context-aware, persona-driven, grounded in your data. Not a glorified FAQ — a useful conversation partner.
Classification & Extraction
Categorize tickets, extract data from documents, route requests, flag anomalies. AI that handles the tedious work your team shouldn't.
Fine-Tuning & Optimization
When prompting isn't enough. Custom model training, distillation, and optimization for your specific domain and data.
AI Infrastructure
Model routing, fallbacks, rate limiting, cost tracking, evaluation pipelines. The unsexy plumbing that makes AI reliable at scale.
From Use Case to Production
Define the outcome
Not "add AI" — what specific problem does it solve? We scope the use case, pick the right approach, and set measurable success criteria.
Build & evaluate
Iterative development with continuous evaluation. We measure accuracy, latency, and cost at every step — not just at the end.
Deploy & monitor
Production infrastructure with logging, metrics, and alerts. Model drift detection. Cost dashboards. AI that stays reliable after launch.
Don't Take Our Word for It
Niro helped me turn a concept into a fully functioning Minimum Viable Product which I will be proud to take to stakeholders, potential collaborators and funders. The speed of development only enhanced the design quality because tweaks were so quick to make. Moreover, he rapidly helped with: - design & userX for an EdTech product for children, young people and adults - keeping the MVP lean and focused but without limiting its capacity to grow and be developed in the future. - packaging it up so I can take it to a different developer in the future if needed. The Iron Mind approach is to thoroughly explain the technology behind the design decisions. As a result, I felt that we not only built a working product from first principles, but I was upskilled along the way! This was my first time working with Niro and I hope not the last!
Niro created an excellent website, exactly to our specifications, and did so qiuckly. The AI assistant he built is intuitive and allows us to change and further develop our online presence. His skills are impressive and he was highly responsive and charming in all our interactions.
For years, Niro has been my go-to expert for building CRM systems, structuring databases, and developing clear strategies for managing client relationships in a truly organized way. With IronMind AI, that vision has fully come together. The platform creates a clean, streamlined ecosystem that brings outreach, CRM, and day-to-day operations into one cohesive flow. What really stands out is the ability to solve problems quickly and approach challenges from fresh, practical angles—removing obstacles that have been slowing things down for years. I highly recommend working with IronMind AI to anyone looking to elevate their systems, simplify their workflow, and move to the next level with clarity and efficiency.
Iron Mind built us a complete SDR performance dashboard in 4 days. It integrates SalesLoft and HubSpot in real-time, tracks KPIs, and gives us full visibility into team performance—something we'd been trying to solve for months. Their use of agentic coding is next level. What normally takes weeks, they delivered in days without sacrificing quality.
What Ironmind and Niro Knox pulled off for me was unreal—my custom secret network proxy app went from idea to fully running in a single day, right when my business needed it most. The speed, precision, and execution weren’t just impressive—they were business-saving, and honestly felt like having an unfair advantage on demand.
Working with Ironmind and Niro was a game-changer for us at KaizIn. I had a vision: a fast, AI-powered personal branding platform that could generate LinkedIn covers, post creatives, and YouTube thumbnails in under a minute. They didn’t just execute, it felt like they were building alongside us. They nailed both the product and the experience. If you're building something in AI, you want a team like Ironmind.
We truly are in a new dawn where an entire backend system was built for us in less than a week. We are incredibly pleased with the work done on our website. From the start, the process was highly professional, quick, and thorough. The developer adapted the design completely to our specific requirements, ensuring the final product aligned perfectly with our vision. Beyond the aesthetics, we were impressed by the technical execution—the code is well-optimized for performance, and the site was fully prepped for SEO right out of the gate. If you are looking for a developer who is reliable, detail-oriented, and capable of delivering a tailored, high-performance site, we highly recommend their services. We couldn’t be happier with the result!
Frequently Asked Questions
How do you add AI features to an existing product?
The process starts with a technical audit of your existing codebase and product. We identify the highest-value AI insertion points — search, content generation, classification, recommendations, or conversational interfaces — and scope each as a discrete feature module. AI features are built as clean backend services (FastAPI or Next.js API routes) with well-defined contracts, so they integrate without destabilising your existing product.
Should I fine-tune a model or use prompt engineering?
Prompt engineering with retrieval (RAG) solves 80–90% of use cases without the cost and maintenance burden of fine-tuning. Fine-tuning is appropriate when you need a specific output style, proprietary domain knowledge that cannot be retrieved at inference time, or lower latency on a smaller, specialised model. We evaluate both options during scoping and recommend the approach with the best return on engineering investment for your situation.
How much does AI feature integration cost?
AI feature integrations start at $35k for a production-ready, well-scoped feature (LLM integration, RAG pipeline, or AI agent). Simple AI features — LLM-powered search or content generation without retrieval — can come in lower at $15k–$25k depending on complexity. All pricing is fixed-scope, fixed-price. Ongoing LLM API costs (OpenAI, Anthropic) are billed by the provider directly and are separate from project fees.
What LLM providers do you work with?
We work with OpenAI (GPT-4o, GPT-4.1), Anthropic (Claude Sonnet, Claude Opus), Google (Gemini Pro), and open-weight models (Llama, Mistral, Qwen) via vLLM or Ollama for on-premise or cost-sensitive deployments. Provider selection is driven by your performance, cost, data residency, and latency requirements — not by vendor relationships. We also implement LLM routing so you can fall back or switch providers without rewriting application logic.
How do you evaluate AI feature quality before shipping?
Every AI feature ships with an evaluation suite: automated test sets covering correctness, edge cases, and failure modes; LLM-as-judge scoring for open-ended outputs; latency and cost benchmarks; and human spot-check protocols. For RAG systems we measure retrieval precision, faithfulness, and answer relevance. Evaluation results are shared with you before production deployment so you have objective data on what you are shipping.
Let's Build Something Intelligent
Tell us what you're trying to solve with AI. We'll tell you what's feasible, what approach we'd take, and how fast we can deliver.
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AI is only as good as the
engineering behind it.
Ours is battle-tested.