AI Apps Platform

AI Apps Platform

Production AI, Managed for You

Ship LLM-powered applications in days — we handle the infrastructure, you own the product.
Book a Free Demo See Pricing

30-min scoping call. No commitment required.

Architecture

How it Works

A fully managed container stack — your app talks to our APIs, we operate everything underneath.
Your App
REST / WebSocket
Nginx Gateway
TLS · Rate limit
Ollama LLM
Llama · Mistral · Gemma
Vector Store
Qdrant · Chroma · Weaviate
Docker Swarm Portainer Let's Encrypt TLS Persistent Volumes GPU-ready nodes AU / India / US DCs

Use Cases

What You Can Build

Common patterns we deploy and operate for customers.
RAG Chatbot

Embed your documents, index them in Qdrant, and serve a private LLM chatbot over your own data — no data leaves your stack.

Ollama Qdrant LangChain / LlamaIndex
Semantic Search

Replace keyword search with vector similarity. Embed your product catalogue, KB articles, or support tickets for instant relevant results.

Embedding model Chroma / Weaviate REST API
AI Agent Pipeline

Orchestrate multi-step agents — tool use, web search, code execution — running on managed containers with API endpoints your frontend calls directly.

Llama 3 / Mistral Function calling Portainer
Document Intelligence

Extract, summarise, and classify PDFs, contracts, or invoices at scale using open-source LLMs — fully offline, fully private.

OCR pipeline Ollama Vector indexing
Data & Analytics Assistant

Natural-language queries over your databases or data warehouses — convert plain English to SQL or pandas, return structured results.

Text-to-SQL Gemma REST endpoint
Multilingual NLP

Translation, sentiment analysis, and content moderation across languages — running on dedicated nodes without per-token API costs.

Multilingual models Batch inference GPU-optional

What We Handle

You Build, We Operate

  • Model deployment — pull, quantise, and serve any Ollama-compatible model on request.
  • Vector database setup — provision Qdrant, Chroma, or Weaviate with persistent storage and collection management.
  • TLS & API gateway — every endpoint gets HTTPS, authentication headers, and rate limiting out of the box.
  • Monitoring & restarts — container health checks, auto-restart on failure, uptime alerting.
  • Backups & snapshots — scheduled volume snapshots so your vector indices and model weights are safe.
  • Scaling — add replicas or migrate to GPU-ready nodes without downtime as your workload grows.
  • Pipeline integration — we set up LangChain, LlamaIndex, or custom orchestration code alongside the infrastructure.
  • Dedicated engineer — a real person answers questions about your stack, not a ticket queue.

Pricing

Custom Quotes

Pricing depends on models, node size, and pipeline complexity — book a call and we'll scope it together.

Starter

Custom quote

  • 1 Ollama model (CPU)
  • 1 Vector DB instance
  • REST API endpoint
  • Let's Encrypt TLS
  • Portainer access
  • Email support
Book a Call
Most Popular

Production

Custom quote

  • Multiple models & replicas
  • Qdrant + Chroma / Weaviate
  • RAG pipeline setup
  • GPU-ready nodes available
  • Monitoring & auto-restart
  • Dedicated engineer support
  • AU, India & US data centres
Book a Free Demo
30-min call, no commitment.

Enterprise

Custom quote

  • Private cluster (your VPC)
  • Custom model fine-tuning
  • SLA-backed uptime
  • Batch inference pipelines
  • Compliance & data residency
  • On-call engineer
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F.A.Q

Common Questions

Which LLMs do you support?

Any model available via Ollama — Llama 3, Mistral, Gemma, Phi-3, Qwen, and many others. We can pull specific quantisations (Q4, Q8) to match your memory budget.

Do you support GPU inference?

Yes. GPU-ready nodes are available for latency-sensitive or large-model workloads. Mention your model size and throughput requirements during the scoping call and we'll recommend the right node type.

Is my data kept private?

Completely. All inference happens on-premise within your container stack — nothing is sent to OpenAI, Anthropic, or any third-party LLM provider. You control your data residency.

Can you integrate with my existing codebase?

Yes. We expose standard REST (and OpenAI-compatible) endpoints so your existing Python, Node, or any HTTP client can connect without changing your code. We also help wire up LangChain or LlamaIndex if needed.

How long does setup take?

A standard stack (one LLM + one vector DB + API endpoint) is typically live within 1–2 business days after the scoping call. Complex pipelines with custom fine-tuning or multi-region setups take longer — we'll give you a timeline upfront.

Ready to ship your AI application?

Book a free 30-minute call. We'll scope your use case, recommend a stack, and give you a fixed quote.

Book a Free Demo