Traditional Approach
- Traditional data tools
- Traditional ML/LLM tools
- Isolated agentic solutions
18+ months · 3 specialist teams · $2M+
Data lifecycle · MLOps · LLMOps · Agentic AI – One unified platform
Your entire
intelligence stack.
One conversation
away.
Datasynaize unifies the entire intelligence lifecycle from raw data to deployed models to autonomous agents in one platform.
No special skills. Just ask.
Enterprise Intelligence OS
Hello, I'm your Enterprise Intelligence OS backed by your full data fabric, every model in production, and all running agents. Ask me anything. No special skills needed.
Ask Your Enterprise Intelligence OS
Powered by DataSynaize AI·SOC 2 certified
SOC 2 TYPE II
GDPR
HIPAA
EU AI ACT
FINRA
ISO 27001
CCPA
EXPLAINABILITY
AUDIT TRAILS
DATA LINEAGE
MODEL GOVERNANCE
AGENT AUDIT
BIAS DETECTION
ACCESS CONTROL
SOC 2 TYPE II
GDPR
HIPAA
EU AI ACT
FINRA
ISO 27001
CCPA
EXPLAINABILITY
AUDIT TRAILS
DATA LINEAGE
MODEL GOVERNANCE
AGENT AUDIT
BIAS DETECTION
ACCESS CONTROL
Enterprise Intelligence OS at your fingertips
Where data becomes intelligence.
And intelligence acts.
Datasynaize is not just a platform. It's your Enterprise Intelligence OS ask it anything across data, models, and agents. It understands your entire organization's intelligence fabric.
Datasynaize Enterprise Intelligence OS
- Data Fabric — data lifecycle, governed
- ML Fabric — MLOps + LLMOps, unified
- GenAI Fabric — autonomous, observable
Days not months · No specialist skills · Chat interface
Time To First Value
Traditional setup18+ months
Datasynaize Enterprise Intelligence OS7 Days
One platform. Your choice of consumption.
Use everything.
Or just what you need.
Datasynaize is architected for maximum flexibility. Adopt the full unified intelligence fabric from day one or drop individual modules into your existing enterprise stack as plug-and-play components. No rip and replace.
◇
Mode 1
Unified Intelligence Fabric
Adopt Datasynaize as your complete enterprise intelligence operating system. Data lifecycle, MLOps, LLMOps, and Agentic AI Suite all work together from a single control plane compounding in value as each layer feeds the next.
- Data Fabric governs all data every model and agent draws from the same trusted source
- ML Fabric trains, deploys, and monitors models on clean governed features automatically
- Generative AI Fabric acts on live data and model outputs autonomous decisions, fully audited
- One governance layer SOC 2, GDPR, HIPAA, EU AI Act across all three
Intelligence flows automatically
Data Fabric→
ML Fabric→
GenAI Fabric→
Outcomes
Value compounds. Every layer makes the others smarter.
⌘
Mode 2
Modular Plug-and-Play Components
Already have Snowflake, Databricks, or SageMaker? Drop any Datasynaize module into your existing stack as a standalone component. Each platform is fully self-contained, API-native, and designed to integrate without disruption.
Data Fabric standalone
Drop into any stack as a data lifecycle + feature store layer
ML Fabric Suite
Plug MLOps + LLMOps into existing data infrastructure
Generative AI Fabric standalone
Add autonomous agents on top of your current models and data
Works with your existing stack
SnowflakeDatabricksSageMakerKafkaAzure MLdbtMLflowLangChainBigQueryVertex AI
No rip-and-replace. Integrate in days, not quarters.
Start with Data Fabric
Drop into your stack as a data lifecycle layer. Works with what you have.
Add when ready
Add ML Fabric
Plug MLOps + LLMOps into the data foundation. Models start getting smarter.
Add when ready
Activate GenAI Fabric
Autonomous agents act on your data and models. The full unified fabric unlocks.
Start anywhere. Add modules as your needs grow. Arrive at the full intelligence fabric on your terms.
Talk to an architectYour data stops being a liability.It becomes your weapon.
Most organizations drown in data they can't trust. Datasynaize's Dangles layer turns raw, scattered data into a governed, versioned, continuously fresh intelligence foundation the bedrock every model and agent builds on.
99.2%
Data Quality
4.7TB
Processed / Hr
847
Features Live
Ingesting S3 - BigQuery - Kafka
12 sources
Data quality pipeline
0 violations last 24h
Lineage graph
847 features tracked end-to-end
Data governance
GDPR - CCPA - HIPAA compliant
End-to-end data lifecycle governance
Ingest, transform, validate, version, and govern data across every source - batch, streaming, and real-time.
Feature store with automatic lineage
847 features, fully versioned, always fresh. Every model knows exactly what data it was trained on.
Data quality that compounds
99.2% quality scores maintained automatically. Bad data never reaches your models. Ever.
Multi-source, multi-cloud, multi-format
S3, BigQuery, Snowflake, Kafka, APIs - unified under one governance layer with zero pipeline glue code.
Why unified matters
Every competitor makes youstitch three toolstogether.
The stitching is where value dies. Data quality issues don't reach your MLOps team. Model outputs don't feed your agents. Agents operate on stale data. Datasynaize eliminates the gaps.
The fragmented approach
Traditional data tools
Traditional ML/LLM tools
Isolated agentic solutions
Custom glue code + 3 data contracts
Value lost at every integration seam
Enterprise intelligence OS
Data Fabric full data lifecycle, governed
ML Fabric MLOps + LLMOps + Agentic AI
GenAI Fabric autonomous, observable
One platform. Zero integration debt.
Value compounds across all three layers
Continuous intelligence
The loop that never stops learning
Every agent action feeds back into the data layer. Every outcome retrains the models. The platform gets smarter every hour you use it no manual intervention required.
Full stack observability
See everything, from byte to decision
Data lineage -> feature provenance -> model explainability -> agent audit trails. Complete observability across the entire intelligence lifecycle every layer, every step.
Governance built in
Compliant by default, not by effort
GDPR, CCPA, HIPAA, SOC 2, and EU AI Act compliance baked into every layer. Regulators get audit reports in one click. Your team doesn't lose sleep.
Deployment velocity
Hybrid Orchestration Engine
The average DataSynaize team deploys a new model to production in 4.2 hours vs the industry average of 3.4 weeks. That's the unified platform effect.
Multi-cloud, multi-framework
Your infrastructure. Our intelligence.
AWS, Azure, GCP, or on-premises. PyTorch, TensorFlow, HuggingFace, LangChain. DataSynaize adapts to your stack not the other way around.
Cost intelligence
Know what your AI costs before it runs
Real time compute cost tracking, budget guardrails, and inference cost optimisation across models and agents. FinOps for AI, built in. No surprises on your cloud bill.
Why users love our product video
See Datasynaizein action.
Teams running on Datasynaize
Data is speaking.Models are listening.Agents are acting.
Real outcomes. No stock photography. No fabricated metrics.
4.2hrs
Model to production - was 3.4 weeks
"We spent two years stitching Databricks, MLflow, and LangChain together with custom glue code. DataSynaize replaced all three in six weeks. The integration debt alone was costing us $400K a year."
R
Rajesh Kumar
Chief Data Officer, Global BFSI Enterprise
340x
More decisions per minute - vs manual
"Our agents process 340 pricing decisions per minute that used to take three analysts a full day. And every decision is audited, explainable, and traceable back to the data that drove it."
A
Ananya Mehta
Head of AI, Tier-1 Insurance Platform
$4.2M
Pipeline-attributed value - Q1
"The moment data quality, model performance, and agent outcomes were all visible in one dashboard, our AI investments became justifiable to the board. DataSynaize made AI a profit centre, not a cost centre."
S
Sarah Thompson
VP Analytics, Fortune 500 Retailer
Ready to unify
Stop stitching.Start Compounding.
14 days free. No credit cards.
Data lifecycle, MLOps, LLMOps, and Agentic AI Suite in one platform that gets smarter every day.
SOC 2 Type II - GDPR - HIPAA - EU AI Act compliant - Multi-cloud