How We Build Technology
Engineering the future of AI products built to work in the wild. From multi-agent systems and RAG to cloud-native data pipelines, our stack is engineered for reliability, scale, and real ROI.
Our Philosophy
We operationalize innovation. Every line, pipeline, and model is designed for real-world chaos: spikes in scale, messy data, shifting APIs, and tight founder timelines.
The result: faster MVPs, resilient platforms, and measurable ROI.
Real-World Focus
Designed for real chaos: spikes in scale, messy data, shifting APIs
Speed to Market
Faster MVPs without sacrificing quality or scalability
Resilient Platforms
Built to handle production loads and edge cases from day one
Measurable ROI
Every decision tied to business outcomes and value delivery
The Four Pillars
Enterprise-grade AI infrastructure that scales with your ambitions
Multi-Agent Systems
Proven patterns for agents that think, tool-call, and collaborate
Production RAG
GraphRAG, rerankers, hybrid search beyond basic embeddings
Guardrails & Governance
PII masking, jailbreak prevention, cost limits, audit trails
Cloud-Native Pipelines
Distributed compute, vector DBs, streaming, async everything
Multi-Agent Systems
Purpose-built agents with specialized tools, memory systems, and collaborative workflows that handle complex, multi-step tasks autonomously.
The Cognilium Stack
Battle-tested infrastructure powering 100+ production AI deployments
Core Technology Pillars
Generative AI & Agentic Systems
Multi-agent orchestration with production-grade RAG
RAG at Scale
Hybrid retrieval, structured outputs, evidence citations for millions of documents
Multi-Agent Systems
CrewAI, LangChain, LangGraph, SuperAGI orchestration
Custom LLMs
Fine-tuned LLaMA-3, Mistral, Gemma, Whisper, Phi with private deployments
Guardrails
Schema validation, fact-checking bots, explainable AI dashboards
Key Technologies
Our Technology Arsenal
LLMs & Models
Vector & Search
Data & Storage
Infrastructure
End-to-End Flow
Resilient pipelines normalize data, retrieval applies policies, agents orchestrate tools, models generate within constraints, results are verified, actions run via APIs, and everything is traced, evaluated, and cost-guardrailed.
How It Works
Data Pipeline
Ingest from any source, clean and normalize, store in optimized formats for retrieval
AI Processing
Hybrid retrieval with GraphRAG, multi-agent orchestration, constrained generation with guardrails
Action & Monitoring
Execute via APIs including NL to SQL, continuous observability, cost optimization
Proven Track Record
Real results from real deployments across Fortune 500s and high-growth startups
100+ Production AI Projects
Battle-tested implementations across industries
50+ Live Deployments
Running at scale in production environments
10M+ Records/Week
Data pipelines processing at enterprise scale
96%+ Uptime SLA
Enterprise-grade reliability and performance
Tech in Action
Real implementations delivering measurable business outcomes
Retail GenAI Insights
Real-time RAG across fragmented e-commerce & ERP data
Dyco Inc.
Agentic chatbot for sales, invoices, and Zoom transcript Q&A
Vorta (Product)
Orchestration engine unifying meetings, Slack, docs into searchable knowledge
Outcomes You'll Feel
Real results that impact your business from the first deployment
Speed
MVPs in weeks—not quarters
Ship faster with battle-tested components and proven architectures
Scale
Built for spikes, messy data, shifting APIs
Infrastructure that grows with your business without breaking
Clarity
Dashboards, SLOs, explainable AI
No black-box spaghetti — full visibility into every system
ROI
Measurable impact from day one
Every technical decision tied to business outcomes