AI needs unified data to work
Everyone talks about AI agents, fine-tuning, automation—but they all need data. Models need data to train. Workflows need data to process. Agents need data to decide and act. We unify your siloed data so AI can actually deliver.
Not sure where to start? Ask us →
Why you need unified data
Every AI initiative depends on data. Without a foundation, you're building on sand.
AI Agents need data to act
Agents make decisions based on what they see—siloed data means blind spots and wrong calls
Models need data to learn
Fine-tuning and training require clean, consistent data—garbage in, garbage out
Workflows need data to process
Automation breaks when data is fragmented across systems that don't talk
Insights need the full picture
Real-time, accurate analytics require unified data—not spreadsheets stitched together
Why Softmax for Data Foundations
We've been unifying data since our days as a Segment partner—before Twilio acquired them. Today we're certified Databricks partners and AWS ML service providers.
Databricks lakehouse experts
Certified partner who can implement the lakehouse architecture to unify your data properly.
As a certified Databricks partner, we implement the lakehouse design pattern that unifies your siloed data—CRM, POS, inventory, marketing, you name it—into a single source of truth your AI systems can actually consume.
AWS data unification too
As an AWS ML service provider, we can build the same unified data layer on AWS services.
Not on Databricks? No problem. As an AWS Machine Learning service provider, we build unified data foundations using AWS services—Glue, Redshift, S3, Lake Formation—whatever fits your stack.
We build AI that consumes this data
We know what AI needs because we build agents and models that use these foundations.
Most data consultants stop at the data layer. We build the AI agents and ML models that consume this data—so we know exactly what clean, unified data needs to look like for AI to work reliably.
What We Build
Multi-Source Unification
One place for everything
Unify CRM, POS, inventory, marketing, and other siloed data into a single source of truth.
We consolidate data from all your systems—CRM, POS, inventory management, ads platforms, email lists, and more—into one unified data layer. No more stitching spreadsheets together.
Unified a retailer's CRM, POS, inventory, ads data, and newsletter system into a single foundation for AI agents to consume.
Lakehouse Architecture
Databricks or AWS
Implement the lakehouse design pattern on Databricks or build equivalent data layers on AWS.
As certified partners, we implement proper lakehouse architecture—Delta tables, medallion architecture, Unity Catalog—or build the equivalent on AWS with Glue, Redshift, and Lake Formation.
A governed, scalable data foundation with lineage tracking and access controls.
AI-Ready Data Layer
Built for agents and models
Data foundations designed for AI consumption—not just dashboards and reports.
We design with AI in mind: clean tables, stable schemas, and the context layer your agents need. Because we also build the AI systems that consume this data, we know exactly what they need.
Your AI agents can query unified data and make accurate decisions—not guess from fragmented sources.
How we build your foundation
Databricks Lakehouse
Certified partner—we implement Delta Lake, Unity Catalog, medallion architecture, and proper governance.
AWS Data Stack
ML service provider—Glue, Redshift, S3, Lake Formation for unified data on AWS.
Funnel.io for Marketing
Quick turnaround on marketing data unification—ads, social, email, analytics all in one place.
AI That Consumes It
We build the agents and models that use this data—so we know exactly what your foundation needs.
References and architecture walkthroughs available on request.
What we ship
Not one-off scripts. Foundations your team can run, monitor, and trust.
Both include:
How we work
Strategy
Choose the first data domain that unlocks value, define success, and map sources and constraints.
Build
Ship a working slice quickly, then harden: quality checks, governance, lineage, observability.
Launch
Operationalize it: documentation, alerts, and ownership so it stays reliable.
Ready to unify your data?
Book a discovery call and we'll discuss:
- Which data sources to unify first
- Databricks vs AWS—what fits your stack
- How to make your data AI-ready
Not sure where to start? Ask us →