Artificial intelligence · intelligence
Stop talking about AI.
Start running it.
Most businesses end up with a chatbot nobody uses. We build AI that plugs into your actual workflows and replaces the manual work burning your team's hours right now.
Grounded in your data. Private by default. Yours to run.
How retrieval-augmented generation runs
Six stages. Click each one to see the code.
This is what powers every RAG system we ship. The depth is the difference between a chatbot that hallucinates and one that cites sources.
Stage 01
Ingest
Your data, structured.
We pull from every system you keep documents in. SharePoint, Confluence, S3, Notion, file shares, ticket exports. PDFs, Word, Markdown, transcripts. Versioned so we know when a policy changes.
from imber.ingest import DocumentLoader
loader = DocumentLoader(
sources=[
"sharepoint://policies",
"s3://contracts",
"notion://kb",
],
formats=["pdf", "docx", "md"],
track_versions=True,
)
docs = loader.load()
# 10,234 documents ingested in 4m 12sClick any stage to see what we actually run
What we build
Six things AI is genuinely good at.
RAG
RAG Pipelines
Your documents, policies, knowledge base turned into a searchable brain. Plain-English questions, grounded answers cited back to the source. No hallucinations.
AGENTS
AI Agents & Workflows
Autonomous agents that read, extract, decide, act. Read an email, pull the data, update the CRM, draft the response, flag exceptions. Digital employees that work the third shift.
CHATBOTS
Custom Chatbots
Conversational AI trained on your data, your tone, your products. Knows the return policy, the pricing tiers, the troubleshooting steps. When it doesn't know, it says so.
PRIVATE
Private LLM Deployment
Models running on your infrastructure. Ollama, vLLM, GPUs you control. Your data stays inside your network. We handle provisioning, model selection, optimisation.
VISION
Computer Vision & OCR
OCR that actually works. Invoice extraction, receipt parsing, ID verification, image classification. Feed a stack of PDFs in, structured data out. Zero manual entry.
STRATEGY
AI Strategy & Readiness
Where AI saves you money before you spend a cent. We audit workflows, rank tasks by automation potential, deliver a prioritised roadmap with estimated ROI.
What changes when AI shows up
Real wins. Not slide-deck dreams.
Support team answering the same 50 questions
Before
5 agents spending 60% of the day on repeat queries. Copy-pasting from a Word doc 3 years out of date.
After
RAG chatbot handles 80% from live knowledge base. Response time: 4 hours → 30 seconds. Agents focus on hard cases.
3 hours/day copying between systems
Before
Admin pulling reports from one system, reformatting in Excel, uploading to another. Every day. For years.
After
Agent monitors source, extracts, transforms, pushes to destination every 15 min. Zero human involvement.
10,000 documents nobody can search
Before
Company policies, contracts, manuals in SharePoint folders nobody remembers. People ask around or start fresh.
After
Every document chunked, embedded, searchable. Type a natural-language question, get the paragraph with source link.
Email triage eating manager time
Before
Manager spends first hour reading and routing 50+ emails. Half are routine but all need reading.
After
Classifier categorises by urgency, drafts responses to routine, flags the rest. 50 emails → 8 to handle.
The stack
Our working stack.
LLM Providers
Claude (Anthropic) · GPT-4o (OpenAI) · Llama 3 (Meta) · Mistral · Ollama for local.
RAG & Vector DBs
pgvector · Qdrant · Weaviate · ChromaDB. LangChain / LlamaIndex for orchestration.
Agent Frameworks
LangChain Agents · CrewAI · AutoGen · custom Python · n8n for visual workflows.
Embedding Models
text-embedding-3 · Cohere Embed · BGE · all-MiniLM. Fine-tuned for domain when it matters.
Deployment
Docker · Kubernetes · AWS/Azure/GCP · Ollama on-prem · vLLM for high-throughput.
Integration
REST · webhooks · WhatsApp Business · Slack · Teams · CRM connectors · email pipelines.
How a build runs
Five stages from idea to in-production.
Assess
Map your processes, rank the highest-ROI AI opportunities. We hunt wasted time. Impressive-demo AI doesn't pay rent. You get a ranked list with estimated savings per use case.
Prototype
Proof of concept on your real data. Real results. We measure time savings, accuracy, edge cases before committing to a full build.
Deploy
Production deployment on your infra or ours. Integrated through APIs and webhooks. Monitoring, logging, fallback handling built in from day one.
Train
Your team learns prompt engineering, output verification, when to trust AI vs double-check. We hand over the tool plus the habit of using it.
Iterate
Monitor accuracy, gather feedback, refine prompts, expand to new use cases. AI gets better with data. We make sure yours does.
Tell us where the time goes.
We will tell you what AI saves.
Free 30-minute audit. We map the workflows eating your hours, rank automation opportunities by ROI, and show you what a real AI build looks like in your business.