Warehouse-Native AI Models for Growth & Retention
Pre-Built production-ready AI models deployed in your cloud in weeks, not months. Train on 100% of your data, inspect every decision, and run models entirely inside your AWS, GCP, or Azure environment.
The Problem: AI Without Real Intelligence
Most organizations rely on AI features built into tools. These systems score customers using generic, black-box models that don’t learn across data sources.
Powerful models stuck in Data Science environments.
Easy-to-use tools you can’t fully trust.
Either way, intelligence is disconnected from activation.
That’s where Syntasa AI Models come in.
The Solution: What If You Could See and Control Your AI?
Most AI forces a tradeoff between depth and speed. Syntasa removes that tradeoff.
Run transparent (“glass-box”) AI models directly on your data — inside your cloud — with no black boxes and no vendor lock-in.
Own the Intelligence
Your models run where your data lives.
You control the logic, learning, and IP — not a third-party tool.
From Model to Action, Instantly
Data teams build in Python. Marketing teams activate in clicks. No long handoffs. No months of engineering.
Real AI. Fully visible. Ready for action.
Why Enterprises Choose Syntasa's AI Models
Most AI platforms force a trade-off. Fast SaaS delivers quick results—but locks you into black-box models. DIY ML offers flexibility—but costs time, money, and scale.
Syntasa delivers both speed and control.
Glass-Box Transparency
- Inspect and audit model logic
- Tune parameters to your business rules
- Full IP ownership — no black boxes
No Volume-Based Pricing
- No MTUs, no sampling limits
- Train on 100% of historical data
- Accuracy improves without cost penalties
Runs in Your Cloud
- Zero data egress
- No vendor access to PII
- Meets strict security & compliance needs
Composable by Design
- Deploy only the models you need
- Prove ROI → add more later
- No forced bundles or shelfware
Decision-Ready Models for Real-Time Growth
Two Model Families. Dozens of Real-Time Decisions.
Customer AI Models
Predict behavior → trigger action instantly
Churn Detection
Predict customer attrition before it happens
On-The-Fence Detection
Identify real-time hesitation
Cart Abandonment
Focus spend on recoverable carts
Price Sensitivity
Discount only when necessary
Channel Preference
Reach users where they engage
Cohort Detection
Auto-create behavioral micro-segments
Product AI models
Optimize revenue at the moment of purchase
Product Recommendations
Real-time cross-sell & upsell
Category Affinity
Personalize content and layouts
Review Summarization
Extract sentiment and themes at scale
DIY AI Studio (Bring Your Own Model)
Code Natively:
Data scientists can write Python/TensorFlow code directly within the Syntasa interface to build and train models on live warehouse data.
Import External Models:
Have a model already built in a local environment? Import it as a source, wrap it in a Syntasa pipeline, and automate its output for downstream activation.
Proven Results
Real Impact, Real Numbers
Global Electronics Brand
Solving Manual, Unscalable & Non-Reactive Product Bundling
The Execution
Deployed Collaborative Filtering and Natural Attach models to drive recommendations based on real-time user behavior.
Result
3x
Add-to-Basket Rate
2x
Product Coverage | 32% → 72%
Enterprise Security Technology Provider
Fixing Eroded Margins Due to Generic Discounts
The Execution
Using Real-time Tags classified users by intent, showing discounts only to on-the-fence users while protecting margins on high-intent traffic.
Result
14%
Low-Intent Uplift
7%
Product Coverage | 32% → 72%
Models Across the Customer Journey
Built for Every Stakeholder
For Data Teams
- Full code access & auditability
- No proprietary schemas
- Train on 100% of data
- You own the IP
For Marketing & Growth Teams
- Pre-built models, fast deployment
- Real-time activation
- Natural language interfaces
- Start small, scale fast
For CIOs & Architects
- Zero-copy, in-cloud execution
- Full governance & compliance
- No vendor lock-in
- Works with your existing stack
Choose the Right Starting Point
Different teams start in different places. Syntasa is designed to meet you where you are — and scale with you.
Start with what you need most today
AI Models
Fast, proven predictions
Best if you want fast, proven predictions without building from scratch.
AI Agents
No-code automation
Ideal if you want no-code automation and natural-language activation.
DIY AI/ML Studio
Full control
Built for teams that want full control to design and deploy custom models.
Ready to Deploy Your First AI Model?
Talk to our team about which model will deliver the fastest ROI.
Not sure where to begin?
Talk to our team. We’ll help you choose the fastest path to value—no overbuying, no lock-in.
FREQUENTLY ASKED QUESTIONS
What are Syntasa AI Models?
Syntasa AI Models are pre-built, production-ready machine learning models that deploy directly inside your cloud environment (AWS, GCP, or Azure). They’re designed to predict customer and product behavior in real time, with full transparency into the underlying logic — no black boxes.
How are Syntasa's models different from AI built into my existing tools?
Most SaaS tools include AI features that use generic, black-box models trained on shared data. Syntasa models train on 100% of your own data, run entirely within your cloud, and give you full visibility into how every decision is made. You own the IP — not a third-party vendor.
What does "glass-box" or "transparent" AI mean?
It means you can inspect and audit the model’s logic, understand why it made a specific prediction, and tune parameters to match your business rules. There are no hidden algorithms or unexplained scores.
What models are available?
There are two model families. Customer AI Models cover use cases like churn detection, on-the-fence visitor detection, cart abandonment, price sensitivity, channel preference, and cohort detection. Product AI Models cover product recommendations, category affinity, and review summarization.
How long does deployment take?
Models are designed to go from deployment to production in weeks, not months, because they arrive pre-built and integrate directly with your existing cloud data warehouse.
Can we bring our own models?
Yes. The DIY AI Studio lets data scientists write Python or TensorFlow code natively within Syntasa, or import models already built externally. These can then be wrapped in a Syntasa pipeline and automated for downstream activation.
Who is this built for?
Syntasa AI Models are designed for data teams who want full code access and auditability, marketing and growth teams who want pre-built predictions without engineering overhead, and CIOs who need zero-copy in-cloud execution with full governance.