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Get a Free 30-Day Proof of Concept — we cover the cost.

Free 30-Day Proof of Concept

A Free 30-Day Proof of Concept — On Your Real Data

Bring 2–3 data sources, tell us where the data should end up, and what you're trying to solve. Our team connects it, builds the pipeline, and runs it in DataFuseAI's canvas — at our cost, not yours.

No cost during the POCNo obligation afterCloud, hybrid, or on-premise

DataFuseAI dashboard showing job, pipeline, and connection profile activity

Why It's Free

We'd rather show you a working pipeline on your own data than ask you to take a demo on faith. That's the whole reason the POC costs you nothing — and it's also why we're selective about which workflows we take on. See who this is a good fit for below.

We assess your problem first

A short scoping conversation before anything is built — sources, destination, current process, and what a good outcome looks like — so the POC targets a workflow that actually matters to your team, not a generic demo scenario.

We connect and build it — in DataFuseAI's own canvas

A real pipeline, built on your real sources, in the same product you'd run in production — connectors, transformations, engines, and scheduling included, not a slide deck.

We cover the cost

Compute, transformation, and engineering time during the POC are on us. You only pay if and when you decide to move the workflow to production — there's no invoice for the evaluation itself.

Proof, not a promise

Three real pipelines, built and run in DataFuseAI — not a irrelevant mockups.

Healthcare workflow, completed run

Retail workflow, completed run

60M-row pipeline, production scale

From One Data Problem to a Measurable Result

This is the engagement itself — what happens week by week, not just the product mechanics.

01

Bring Your Workflow

Select one recurring data workflow that's expensive, manual, difficult to maintain, or hard to monitor.

MongoDB + PostgreSQL + Excel → Procurement Reporting
02

We Build It in DataFuseAI

We configure the workflow using Connect → Transform → Validate → Schedule → Monitor — in the real product, not a sandbox.

03

We Run It and Measure

We operate the workflow for real and compare the result against your existing process, against the criteria we agreed on up front.

04

You Decide

Review the results and decide: stop after the evaluation, move the workflow to production, or expand DataFuseAI to more pipelines.

Week 1 — Assess & Connect

Week 2 — Build & Transform

Week 3 — Run & Validate

Week 4 — Measure & Decide

What Your Team Brings

Keep the scope focused. The goal isn't to migrate your entire data estate in 30 days — it's to prove value on one real workflow.

  • One real business workflow
  • 2–3 relevant data sources
  • Sample or approved access to the required data
  • One technical point of contact
  • Information about the current process
  • A clear business or operational objective

We deliberately keep this list short. Most POCs stall not because the technology doesn't work, but because the scope was too broad to evaluate in 30 days — one workflow, evaluated properly, tells you more than five workflows evaluated poorly.

Example
Sources
PostgreSQL + REST API + Excel
Current problem
Operations staff manually combine data every week before reporting.
POC objective
Automate ingestion, transformation, validation, scheduling, and reporting preparation.

What We Help You Evaluate

Connect → Transform → Validate → Schedule → Monitor → Deliver. Our team runs this operating flow on your workflow — you tell us the source, we handle the rest. Each step below is a real screen from the platform, not a mockup — click any image to look closer.

01

Connect

We configure validated connections to your sources — databases, APIs, files, or SaaS platforms.

02

Transform

We clean, join, filter, and shape the data on DataFuseAI's canvas for your exact workflow.

03

Validate

We profile the output and validate it before it reaches anything downstream.

04

Schedule

We set the pipeline to run automatically, on the cadence your workflow needs.

05

Monitor

We give you visibility into every run — succeeded, failed, or in progress.

06

Deliver

We land the result where you need it — your warehouse, Power BI, Tableau, or an AI application.

This isn't the whole platform — see the full data connectors, processing engines, and architecture. The goal of the POC isn't to migrate your whole data platform — it's to prove value on one production-relevant workflow first.

What We'll Measure Together

We agree on success criteria up front, so the result is something you can evaluate objectively — not just a good demo.

Setup Effort

How much work is required to configure the workflow.

Manual Work Removed

Which recurring manual steps get automated.

Pipeline Maintenance

How much custom code or ops work remains.

Failure Visibility

Whether failed or incomplete runs surface sooner.

Reconciliation Effort

Whether comparisons between systems get easier.

Reporting Turnaround

How fast trusted data reaches reporting and analytics.

Operational Handoff

What it takes for your team to run this day to day.

Deployment & Security Fit

How well the setup matches your constraints.

We won't promise a fixed percentage improvement before we've seen your workflow — these eight criteria are what we'll actually measure together, against your current process, during the 30 days.

What Could a 30-Day POC Look Like?

A few starting points from workflows we see most often. Yours doesn't need to match one exactly — it's the shape that matters: a few sources, one workflow, one destination.

Healthcare

Sources

EHR / HIS + Billing + Database

Workflow

Operational or procurement reporting

Output

Validated dataset → Power BI / analytics

Manufacturing

Sources

ERP + MES + CSV / Database

Workflow

Production, inventory, or supplier reporting

Output

Unified operational dataset

Finance

Sources

ERP + Transaction Database + API

Workflow

Data reconciliation

Output

Validated reconciliation / reporting dataset

Retail

Sources

POS + Ecommerce + Inventory

Workflow

Sales and inventory consolidation

Output

Unified reporting dataset

Evaluate DataFuseAI Where Your Data Needs to Run

We'll structure the POC around the deployment model that fits your environment.

Managed Cloud

Run the POC in a managed environment for the most straightforward evaluation.

Private Hosted

Run the platform in a controlled private environment where that's required.

On-Premise

Evaluate closer to the systems and data that must stay inside your infrastructure.

Not sure which fits? See deployment options or tell us in the application below.

Is This a Good Fit for Your Team?

We don't take every applicant — a POC only proves something if the workflow behind it is real.

Good Fit

  • A real, recurring data workflow
  • 2–3 identifiable data sources
  • A named destination or outcome (warehouse, BI, analytics, AI)
  • Someone who can grant access to the data
  • Manual, error-prone, or hard-to-maintain data work today

Probably Not the Right Fit

  • Pure research with no real workflow behind it
  • An expectation of a full enterprise migration in 30 days
  • Sub-second streaming as the primary requirement
  • A one-time file conversion with no recurring need
  • No one internally who can own the go/no-go decision afterward

What You Have at the End of 30 Days

Free doesn't mean informal. Every POC ends with the same concrete set of deliverables.

01

Working Workflow

A scoped DataFuseAI pipeline built around your agreed use case — not a demo environment.

02

Configured Sources

Validated connection profiles for the 2–3 sources you brought, ready to reuse.

03

Automated Execution

Scheduling and execution configured where applicable, running on your cadence.

04

Validation & Monitoring

Run history, data profiling, and operational visibility, demonstrated on your data.

05

POC Results Review

A comparison against the success criteria we agreed on before starting.

06

Production Recommendation

Concrete next steps for production deployment or broader adoption — or a clear no.

The POC Ends With a Decision, Not an Obligation

Every path below is a decision you make after seeing results — not a default.

You leave the POC with a workflow review, the pipeline configuration itself, a results summary against the criteria we agreed on, identified improvements, and a recommended production architecture — whether or not you continue.

Option 1

Stop

No cost, no further commitment. The evaluation is complete.

Option 2

Go to Production

Move the validated workflow into a production DataFuseAI deployment.

Option 3

Expand

Bring more sources, workflows, or teams onto DataFuseAI under an agreement.

Bring Us One Pipeline

Answer in your own words where it's easier — this takes about 3 minutes.

Step 1 of 5About You

By submitting, you agree to be contacted by DataFuseAI about your POC application.

    Frequently Asked Questions

    Yes. Connecting your sources, building the pipeline, running it, and the compute and processing it uses during the 30 days are all on us. There's no cost unless you choose to move to production afterward.

    2–3 real data sources, a clear target or destination for the output, and a short description of the workflow or problem you want solved.

    Yes, where it fits your environment — we'll confirm deployment requirements during the initial assessment.

    No — the POC evaluates one workflow properly. It isn't a full migration of your data estate.

    Access is scoped to the sources you approve for the POC, connected the same validated way DataFuseAI connects any source in production.

    You review the result against what we agreed to measure and decide: stop, go to production, or expand. There's no default obligation either way.

    A demo shows the product. This builds and runs your actual workflow on your actual data.

    Yes. DataFuseAI supports scalable compute through engines like Databricks, Apache Livy, and its native engine — you choose where computation runs, so the POC can execute against your existing compute rather than a separate sandbox.

    Read access (or a representative sample) for the 2–3 sources you bring, and a technical point of contact who can approve connection credentials. We don't need broader access to your systems than the workflow itself requires.

    Typically the assessment and first connections happen within the first few days; the rest of the 30 days is building, running, and measuring.

    Ready to prove it on your own data?

    Start with one real pipeline — free for 30 days. See what changes before you decide anything.