DEEPFINERY
THE REFINERY FOR BUSINESS LOGIC INTELLIGENCE
Why Agentic AI is Stalling
Most never reach production.
Stale Knowledge
LLMs are frozen in time. Logic needs to be fresh, not just retrieved via complex RAG.
Prohibitive Cost
Giant models destroy margins. You can’t run a 100B+ model for every simple transaction.
The Tuning Gap
Building custom models is too hard. Enterprises need to embed logic inside the weights.
The Deepfinery Ecosystem
Ontology Studio
The “Teacher”. Interactively extracts business rules and converts ambiguous text into structured Knowledge Graphs.
Training Studio
The “Refinery”. Fine-tune SLMs (Small Language Models) using LoRA/QLoRA with a no-code interface.
Serving Dashboard
The “Engine”. Host refined models on affordable GPUs with enterprise-grade monitoring and support.
The Path to AGI
Frequency is the Key.
Today’s GenAI creates content based on patterns. Tomorrow’s AGI optimizes outcomes based on goals.
To achieve this, we need frequent training and tuning—a cycle impossible with giant models. Deepfinery enables the shift to Refined Small Models (SLMs) that can be retrained daily to learn from their environment.
Product 1: Ontology Studio
Knowledge Engineering
- Interactive Ingestion: Chatbot agents interview developers to extract precise business rules.
- Graph Visualization: Automatically generates a Knowledge Graph to visualize logic flows.
- Logic Testing: Turn business rules into testable logic APIs immediately.
Product 2: Training Studio
The Model Refinery
- Select Base Model: Choose from Llama 3, Mistral, or proprietary SLMs.
- No-Code Tuning: Configure hyperparams (Epochs, LoRA Rank, Alpha) via simple sliders.
- One-Click Export: Download ready-to-serve containers or .zip files instantly.
Product 3: Serving Dashboard
Enterprise Deployment.
Hosting models shouldn’t require a PhD in DevOps. Our dashboard provides “Hosting as a Service” on cost-effective GPUs.
- Real-time API monitoring and logs.
- Pay-as-you-go inference pricing.
- Seamless integration with OpenShift AI and Kubernetes.
The Logic Refinery Pipeline
Ingest
Docs & PDFs
Distill
Ontology & Rules
Train
Fine-tune SLM
Serve
Low Latency API
Legacy Modernization
Moving from brittle Java/Drools rules engines to adaptive SLMs.
Required for real-time fraud detection and transaction processing.
Data center upgrades driven by the move to Agentic AI (Nvidia).
Revenue Model
TaaS
Training as a Service
$20 / Tuning Job
Pay-as-you-go model tuning for developers and startups.
HaaS
Hosting as a Service
Retail hosting on affordable GPUs. Markup on compute costs.
Enterprise
Solution Support
Licensing for on-premise deployment via OpenShift operators.
Go-To-Market Strategy
Co-sell with Red Hat (OpenShift Operator)
Co-sell with Nvidia (Nemotron Accelerator)
Marketplace: AWS, Azure, GCP
Hardware Partners: AMD, Intel, Nebius
Direct to Devs: Pay-as-you-go API
Sell to Startups as AI Retailer
Roadmap & Financials
Q1 2026: Beta Launch
Ontology Studio release. Onboard first 50 pilot enterprises. RedHat certification.
Q2 2026: Training Scale
Integrate Nvidia Nemotron. Launch TaaS API for public developers.
Q3 2026: Marketplace
Launch on AWS/Azure marketplaces. Release “Deepfinery Edge” for local deployment.
Q4 2026: Autonomous Agents
Self-optimizing pipelines. Goal: 1M+ models tuned.