ML FABRIC · AUTO-RESEARCH · MLOPS · ENTERPRISE INTELLIGENCE OS
Your AI is live. Is it governed? Does it act?
Hallucinations reaching production
Agent decisions / minute
LLM inference cost
Prompts versioned + A/B tested
RAG retrieval quality
Three words. AI governing AI.
Not a wrapper around an LLM API. The enterprise operating layer for LLMs and autonomous agents where AI evaluates AI, AI orchestrates AI, and every output is governed.
Evaluate
AI grades every AI output. Before it reaches anyone.
2,400 test cases per run. Hallucination detection, semantic consistency, instruction following, and regression testing automated, continuous, before and during production. Zero human reviewing every output. The platform does it.
94.2% EVAL ACCURACY
Orchestrate
Multi-agent systems that act, decide, and self-coordinate.
Wire governed LLMs into autonomous, multi agent workflows that take real business actions. Specialised agents per domain. Agent-to-agent communication. Human in the loop gates. One click rollback. 340 decisions per minute every one traceable.
100% AUDITED
Govern
Every prompt versioned. Every agent action logged.
Prompt registry with A/B testing. LLM cost intelligence with model routing. Full agent audit trails with reasoning traces. EU AI Act Art. 9–15. GDPR Art. 22. SOC 2. Governance is the foundation, not a feature you add later.
IMMUTABLE LOG
10 stages. AI evaluating every step.
From model selection to autonomous action — governed and observable at every stage. Click any stage to explore.
Define
Set business intent, constraints, success criteria, and compliance boundaries before any model runs.
Not another AI wrapper. The operating layer.
See exactly what Datasynaize does that no alternative platform — or stack of tools — can replicate natively. Then see the numbers.
WHY DATASYNAIZE
The only platform that does all of this. In one place.
Every alternative requires 4–7 stitched tools, a DevOps team, and months of integration. Datasynaize ships it governed, observable, and production-ready.
| CAPABILITY | Datasynaize | DIY Stack | Azure OpenAI | AWS Bedrock |
|---|---|---|---|---|
| Fine-tune + RAG in same pipeline | ||||
| AI evaluates AI — before production | ||||
| Knowledge Distillation built-in | ||||
| ContextOps — stale chunk detection | ||||
| Multi-agent orchestration + audit trail | ||||
| EU AI Act + GDPR + SOC 2 built-in | ||||
| Quantization with quality gates | ||||
| One platform: Data + ML + GenAI |
CUSTOMER OUTCOMES
Real impact. Measured. Governed. Shipped.
Demand forecasting model was GPT-4o via API — $140k/month spend, no governance, hallucinating 7% of responses.
Distilled GPT-4o into a 7B model. RAG-grounded with ContextOps. Hallucination rate: 0.2%. Cost: $9k/month.
LLMOps + Agentic AI. Unified.
Everything you need to run governed, observable, cost-efficient GenAI at enterprise scale.
Run 2,400+ automated test cases per deployment. Hallucination detection, semantic consistency, instruction-following, and regression testing — all before a single user sees a response.
340 decisions per minute. Every one governed.
12 specialised agents. Coordinated by the Generative Fabric orchestrator. Acting on governed data from Data Fabric,
guided by ML model scores from ML Fabric. Full audit trail on every action.
Every layer feeds the next.
Actions compound.
Generative Fabric grounds itself in governed data and ML intelligence then turns that intelligence into autonomous business action.
Data Fabric
Governs your data estate. RAG retrieves from it. Agents act on it. Every LLM response traceable to a lineage-tracked data source.
ML Fabric
Production ML models. Model scores feed agent decisions churn probability, fraud score, demand forecast all become action signals.
Generative Fabric
LLMOps + Agentic AI. Governs LLMs, orchestrates RAG, routes model calls intelligently, wires autonomous agents that act on everything below.
RAG grounded in governed, lineage-tracked data. Agent decisions use ML model scores as real-time signals. Everything is auditable and traceable.
Every agent action becomes a data point. Every LLM eval improves future routing. The Enterprise Intelligence OS gets smarter every hour it runs.
One conversational interface across all three fabrics. Ask about LLM eval results, trigger an agent workflow, query your data estate without knowing which fabric you're talking to. Nexen orchestrates everything.
Your AI is live.
make it trustworthy.
Connect with our team about LLM evaluation, agent workflows, and governed GenAI with full traceability.