Generic foundation models break when you deploy them as agents. UBIAI fine-tunes your agent components: classifier, retriever, reasoning—and optimizes entire agentic workflows so they handle real production traffic reliably. Build agents that scale.
TRUSTED BY INNOVATIVE TEAMS WORLDWIDE
Foundation models excel at general tasks. But agents need specialized behavior—precise routing, structured planning, reliable tool use. When generic models meet complex agent workflows, they struggle with your schemas, your logic, your production edge cases.
Your generator makes up facts with total confidence. It wasn't trained on your domain knowledge, so it fills gaps with plausible-sounding nonsense that destroys user trust.
Generic models don't know your voice, your terminology, or your output requirements. Every response needs manual editing because the generator can't match your standards.
Works great on 10 examples. Falls apart on 10,000. Generic models can't handle the edge cases, domain jargon, and real-world complexity your users throw at them.
Prompt engineering is a bandaid. RAG alone isn't enough. Your agent components need to actually understand your domain.
Your agent is only as good as its weakest component. Each piece of your agentic workflow can be fine-tuned to understand your domain, your data, and your users. Here's where the magic happens.
Identify which component is failing and fix just that piece
When every component is tuned, errors don't compound—they disappear
Smaller, specialized models outperform bloated general-purpose ones
Stop wrestling with training pipelines and hyperparameters. UBIAI guides you from broken agent to production-ready system, no ML PhD required. Define what you need, upload your data, and let the platform handle the complexity.
Choose which part to fine-tune
Bring your domain-specific examples
We optimize prompts or weights
Ship to production with tracking
Fix the part that's actually broken
Don't retrain your entire agent. Identify which component is failing and fine-tune just that piece. Most teams start with the generator, it's where hallucinations and wrong formatting happen.
"My generator keeps hallucinating product specs" -> Fine-tune on your actual product documentation and customer Q&A pairs
Fast results, then scale to weights
UBIAI starts by optimizing your prompts automatically getting 80% of the gains in minutes. When you need more, seamlessly upgrade to weight fine-tuning for maximum accuracy.
Know if it actually got better
Automatically test your fine-tuned components against your real use cases. See exactly how much accuracy improved before you deploy anything.
Get 80% of the improvement in minutes, not hours. Optimize prompts automatically before committing to full model training.
Hours of trial and error
Test one prompt at a time
No systematic evaluation
Plain English, examples, criteria
LLM judge + augmented data
Proven performance metrics
Test multiple prompt variations in minutes with automatic evaluation
Automated quality scoring across all your test cases
When prompts hit limits, seamlessly upgrade to weight fine-tuning
From training data creation to production deployment, UBIAI provides the complete toolkit for building agent components that actually work in the real world.
Upload domain examples or generate synthetic data for any component.
Label routing decisions, query pairs, and function calls for each component.
Auto-generate realistic variations from existing examples.
LLM-as-judge scores and removes low-quality examples automatically.
Prompt fine-tuning in 15 min, weight training in 2-4 hours.
We choose the best model for your component and budget.
Start with prompt optimization, upgrade to weights when needed.
15-minute prompts for quick wins, 2-4 hour weights for max accuracy.
Deploy via API or export to your infrastructure.
Works with LangChain, LlamaIndex, AutoGPT, or custom frameworks.
Export as GGUF, safetensors, or Hugging Face models.
Track accuracy and latency. Auto-retrain when performance drifts.
Don't start from scratch. Use proven agent architectures and fine-tune them for your specific domain in minutes.
Pre-configured classifier, retriever, and response generator. Fine-tune on your docs and support history to handle tier-1 tickets automatically.
Lead qualification, product recommendation, and objection handling. Train on your CRM data and product catalog for accurate responses.
Semantic search, code snippet generation, and multi-step guidance. Perfect for technical documentation and API references.
Multi-class classification with reasoning. Train on your community guidelines to detect policy violations with high accuracy.
Intent recognition, parameter extraction, and multi-tool orchestration. Connect to your APIs and automate complex workflows.
Query decomposition, multi-source retrieval, and synthesis. Ideal for answering complex questions across large knowledge bases.
We'll help you design the perfect agent architecture for your use case.
Book a Strategy CallFrom exploration to enterprise, we have a plan that fits your goals and grows with your ambitions.
Perfect for getting started with AI personalization.
For growing teams building multiple AI applications with advanced features.
For large organizations with complex requirements and custom needs.
From open-source leaders to proprietary powerhouse, UBIAI supports the models you need. Pick the right foundation for your use case and budget.
Meta's powerful open-source models. Great balance of performance and cost for most use cases.
Efficient European models with strong multilingual capabilities and excellent instruction following.
Industry-leading models from OpenAI. Premium performance for demanding applications.
Google's lightweight open models. Optimized for efficiency and easy deployment.
Alibaba's capable multilingual models with strong coding and reasoning abilities.
Chinese open-source models with exceptional reasoning and coding capabilities at competitive costs.
We support many more open-source and proprietary models.
Request a DemoPrompt engineering has limits. RAG alone isn't enough. The only way to get agent components that actually work in production is to train them on your domain. That's what UBIAI does.
Fix exactly what's broken
We handle the complexity
Agents that actually work
Don’t build another generic model. Build your vision in AI.