AI Integration & LLM Development
Context-aware AI assistants, multi-agent RAG pipelines, autonomous AI agents, and fine-tuned LLMs that plug into your existing business workflows.
What you might face
Your team spends hours on repetitive decisions, data lookups, and reporting that could be automated with AI — you're losing competitive advantage every day.
How we engineer it
We build Retrieval-Augmented Generation (RAG) systems with Pinecone/Weaviate vector databases, connect GPT-4o/Claude to your private data, and deploy multi-step agentic workflows with LangGraph.
The concrete outcome
Production-deployed AI assistant with measurable 40%+ reduction in manual overhead, full observability dashboard, and complete source code ownership.
System Architecture Flow
Hover over the pipeline nodes to inspect our live engineering data-flow breakdown.
Data Ingestion
PDFs, SQL, APIs, and Notion pages are parsed, chunked, and vectorized into Pinecone or Weaviate.
Core Service Capabilities
Concrete engineering features we integrate into your digital footprint.
Multi-Agent RAG Systems
Retrieval-Augmented Generation pipelines connecting your private PDFs, Notion, SQL databases, and APIs to state-of-the-art LLMs with full source attribution.
Autonomous AI Agents
LangGraph-powered agents that execute multi-step workflows, browse the web, call APIs, write code, and verify their own outputs before delivering results.
LLM Fine-Tuning
Custom fine-tuned models on your proprietary data using LoRA/QLoRA — reducing hallucinations and ensuring brand-consistent, domain-expert responses.
AI Observability
Full tracing dashboards via Langfuse or LangSmith — every token, every tool call, every latency spike is visible and auditable in real time.
Secure Private Deployment
On-premise or private cloud LLM deployments using Ollama or vLLM — your data never leaves your infrastructure.
Voice & Multi-Modal AI
Speech-to-text (Whisper), text-to-speech, and vision-capable agents that can read invoices, analyze images, and respond to spoken commands.
Supported Stacks & Infrastructure
We implement custom codebases tailored to your speed, scalability, and integration requirements.
OpenAI & Anthropic APIs
LLM Agent EngineConnecting GPT-4o, Claude 3.5 Sonnet, and local models to automate enterprise operations and chat logic.
Context-aware chatbots, automatic support email replies, and summary generation.
- State-of-the-art reasoning engines
- Tool calling (function invocation) structures
- Multi-modal vision analysis support
Support Agent Stella
A customer agent parsing email logs, querying internal database inventories, and drafting detailed answers.
"Stella handles common support questions beautifully. Human escalation rates dropped by 80%."
AI Model Ingestion Telemetry
Comparing cached semantic retrieval engines against raw LLM completions.
Response Generation Delay
Comparison of engineering benchmarks (Lower is better).
Accuracy Precision
RAG contexts prevent model hallucinations.
Token Overhead
Embedding-cached lookup cuts monthly API costs.
Inference Time
Agent responses render almost instantly.
Data Compliance
Local context layers prevent leakage of database keys.
Common Questions
Everything you need to know about starting a project with this service.