Library 451
AI Engineering Consultancy — Agents, RAG & MLOps
Preview
Your AI at Work
Watch autonomous AI agents handle your business operations in real-time. Four modules, zero human intervention.
Powered by the best in AI & infrastructure
- Claude
- GPT-4
- LLaMA
- Mistral
- Gemini
- Cohere
- LangChain
- LangGraph
- CrewAI
- Vercel AI SDK
- Hugging Face
- Ollama
- ChromaDB
- Pinecone
- Docker
- Kubernetes
- PostgreSQL
- Redis
- Supabase
Services
AI Engineering Services
End-to-end AI systems, from prototype to production.
AI Agents
Software that works while you don't. An agent processes your supplier invoices, triages support tickets, or qualifies inbound leads, following your rules and escalating to a human when judgment is needed.
Prompt Engineering
Same AI, same data, but the customer-facing chatbot suddenly answers correctly 90% of the time instead of 40%. The difference is how you ask. We design, test, and version prompts so your models perform consistently, not randomly.
Fine-tuning
Your industry has its own vocabulary, reasoning patterns, and edge cases. We train a model on your data so it understands your domain like a senior employee, not like a generalist chatbot.
RAG Pipeline
Your legal team asks a question about a clause buried in 10,000 contracts and gets an accurate answer in seconds, with the exact source and page number. That's what RAG does for your organization's knowledge.
MCP Integration
Instead of building a separate integration for each AI tool, one MCP server connects all of them to your internal systems at once. Your AI reads live data from your CRM, triggers actions in your ERP, and works across Claude, ChatGPT, Cursor, and any compatible client.
MLOps & Deploy
Your model works in a notebook. We make it work in production: versioned, monitored, auto-scaling, and gated by quality checks so a bad update never reaches your users.
Capabilities
AI Capabilities at a Glance
Impact
The Business Impact of AI
Faster Delivery
Task completion with AI-assisted workflows
Tasks Automatable
Of employee time through generative AI
AI Models
Benchmarked across providers
ROI
Average return per dollar invested
Process
Our AI Development Process
Audit
01We start by understanding what you actually have. Your stack, your data, your pain points. Not every problem needs AI, and we'll tell you when it doesn't.
Architecture
02Before writing any code, we map the entire system. Which models, how data flows through them, what happens when things break. Everything is documented and agreed upon.
Build
03We ship working demos every week. No black boxes, no surprises. Everything is built against the same constraints it'll face in production.
Ship
04We don't hand over a repo and wish you luck. We set up the infrastructure, the pipelines, the rollback strategies. Then we deploy it ourselves and make sure it holds.
Operate
05Systems degrade silently if nobody's watching. We track performance, cost, and accuracy from day one so problems get caught before your users notice them.
FAQ
AI Engineering FAQ
Start Your AI Project
Tell us what you're working on. We'll review your project and come back with an honest assessment.