Train Your OwnLLM Models.Deploy on Cloud
Pick any open-source model. Bring your documents or data. Fine-tune, deploy on your servers or the cloud — and build AI agents that actually know your business.
Your Model, Not Theirs
Build & deploy custom models that are higher quality, more cost efficient, and faster than generic LLMs on your tasks.
Train a model that analyzes earnings calls and flags sentiment shifts
From raw data to training-ready datasets — automatically
Real-world data is messy, inconsistent, and rarely labeled. ALTAI generates the synthetic data you need, structures it for fine-tuning, and validates quality before a single training step runs.
Ship leaner models that punch above their weight
A model trained on your domain does more with less. You stop paying for general-purpose headroom you never use — and your users stop waiting for it.
Build the Model ThatKnows Your Business
Four steps from your raw files to a deployed, fine-tuned model — no ML team, no infrastructure headaches.
Bring Any Data Source
PDFs, DOCX, CSV, spreadsheets, or plain text — upload directly. Connect databases, MCP servers, or APIs for live ingestion. Preview and validate everything before training begins.
Auto-Generate Training Data
ALTAI turns your raw documents into structured, LLM-ready datasets — Q&A pairs, tool-calling sets, or instruction data. No data engineers needed.
Train Your Model
Pick a base model — Llama, Mistral, Qwen, or any open-source LLM. Train and monitor progress in real time.
Deploy Anywhere, Instantly
One-click deployment to on-prem servers, private cloud, or air-gapped environments. Get an OpenAI-compatible API, built-in chat UI, tool-calling support, and full observability out of the box.
Your Industry Has Specific DemandsYour AI Should Too
Build AI that understands your business, use cases, and processes. Achieve high accuracy, low costs, and compounding IP you fully own.
Compliance and risk intelligence that moves at the speed of regulation
Custom AI for the institutions that can't afford to get it wrong. Frontier models failed 50% of code translation tests. A top-5 U.S. bank is modernizing 100 million lines of legacy code. Open-source models delivered 85% of Sonnet 4.6's quality on codebase comprehension — no proprietary code ever left the bank's environment.
Common Questions
Everything you need to know about ALTAI, from our technology to implementation and security.
Getting Started
You can use a wide range of data sources:
- Documents: PDFs, DOCX, spreadsheets, text files — upload your raw files directly.
- Structured datasets: Bring your own Q&A pairs or instruction sets.
- Synthetic data: Our AfterImage engine can generate training data from your unstructured documents automatically.
Data & Security
Training & Deployment
You choose the deployment architecture that fits your security and performance needs:
- On-Premise: Run on your own physical servers behind your firewall.
- Private Cloud (VPC): Deploy in your isolated cloud environment.
- Air-Gapped: Zero internet connectivity for maximum security.
- Public Cloud: Use managed cloud infrastructure for flexibility.
Pricing & Support
Your Data. Your Models.Your Infrastructure.
You don't need an ML team — you need the right platform
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