What is Edilitics Transform, and why does it matter?

Edilitics Transform is the engine that takes raw, integrated data and makes it usable for analytics, dashboards, and AI - without code, without engineering bottlenecks, and with full governance. It’s not just “visual ETL” - it’s a governed, production-grade transformation layer built to handle real-world complexity with clarity and speed.

Which transformation operations are supported, and are they truly no-code?

Edilitics supports a full range of transformations - data type casting, filtering, joins, aggregations, enrichments, calculated columns, and more. All core operations are fully no-code, with a point-and-click builder that’s actually usable (not a gimmick). For true edge cases, Python scripting is available, but it’s optional, never required.

Does configuring a transformation affect my live data?

No. All configuration and testing happens on an encrypted sample of up to 5,000 rows, extracted in real time from your source. The live data is untouched until you explicitly deploy a transformation flow. If you abandon or don’t save the flow, the sample is deleted - automatically and securely - within 24 hours.

Why aren’t transformations executed directly inside my database or warehouse?

Running logic inside your warehouse can be expensive, opaque, and prone to security or data staging risks. Edilitics extracts data and processes it inside isolated, short-lived VMs - so you avoid compute bloat, have no temp tables, and keep your data estate clean. More importantly: all business logic and governance remain centralized, not scattered across SQL views or stored procs.

Does Edilitics support incremental or CDC-based transformations?

No, and for good reason. Many transformation workflows require joins, group by, or business rules that cannot be reliably computed incrementally without risking stale or incorrect outputs. By running each transformation as a fresh, full extract, Edilitics guarantees accuracy, auditability, and data lineage - critical for analytics and compliance. No guesswork, no silent breakages.

Is any data stored or staged in Edilitics during transformation?

Never. Aside from the short-lived sample used for flow setup (see above), no customer data is ever stored, staged, or retained after a transformation completes. Every job runs in a dedicated, ephemeral VM that’s destroyed on completion - eliminating lingering data risk or surface area for attack.

How do I validate my transformation logic before pushing to production?

Every operation in your flow is previewed on the live sample. You can inspect outputs, debug errors, and iterate as needed before the workflow is saved or deployed. This “preview-first” approach catches logic errors, schema mismatches, and data surprises before anything is committed.

How is compute consumption measured and managed in Edilitics Transform?

Each transformation run is metered down to the second, based on the resources used. You can track usage in real time, get alerts before limits are hit, and purchase additional compute minutes on demand - no forced upgrades, hidden throttling, or unpredictable costs.

What happens if a transformation fails or data is unavailable?

Edilitics fails fast and transparently. If your source schema changes or a job errors out, the pipeline is paused and you’re instantly alerted via app, email, or Slack (if configured). There are no silent failures or ambiguous partial runs; detailed logs enable quick root-cause analysis and remediation.

Can non-technical users automate and govern transformation workflows?

Yes. The entire transformation process - from flow creation to scheduling, monitoring, and auditing - is 100% no-code and role-based. Admins can delegate access, lock down sensitive flows, and ensure governance is enforced at every stage. You don’t need engineering resources to build, manage, or troubleshoot pipelines - analytics teams and domain experts own the logic.

Transform · next release

COMING SOON • MODEL • VALIDATE

Transform is gated until Q1 ’26.

Need an aligned rollout? Talk to the product team so we can slot you in once guardrails lock.

Private beta
Inline Python + visual flows are available only to existing tenants.
Telemetry first
Regression tests, lineage tracing, and compute metering are being tuned.
Launch window
Q1 ’26 is when we flip this page to the full experience.

Talk to product Read transform docs

Flow previewLive sample: 5,000 rows

Step 1
Join (orders ↔ spend)
Validated
Step 2
Filter (Active markets)
2 warnings
Step 3
Python: LTV buckets
Tests passed

Contract & lineage

Output schema28 columns
Downstream consumersDashboards, AskEdi

python step:

df["ltv_bucket"] = pd.cut(
  df.ltv,
  bins=[0, 3_000, 10_000, 25_000],
  labels=["Trail", "Core", "Enterprise"]
)

Flow previewLive sample: 5,000 rows

Step 1
Join (orders ↔ spend)
Validated
Step 2
Filter (Active markets)
2 warnings
Step 3
Python: LTV buckets
Tests passed

Contract & lineage

Output schema28 columns
Downstream consumersDashboards, AskEdi

python step:

df["ltv_bucket"] = pd.cut(
  df.ltv,
  bins=[0, 3_000, 10_000, 25_000],
  labels=["Trail", "Core", "Enterprise"]
)

Why it’s gated

The engine is running - we’re just keeping the lights dim.

Beta tenants are stress-testing contracts, inline Python, and compute metering so launch day feels inevitable - not experimental.

Beta access

Invite-only

We’re working with customers already deployed on Integrate + Replicate.

Telemetry

Full traceability

Every run feeds regression suites, approvals, and lineage dashboards.

Launch signal

Q1 ’26

We’ll swap this teaser for the full experience when GA is certified.

Need coordination?

Bring your architecture, SLAs, and governance asks. We’ll align timelines so your workspace is ready the day Transform opens up.

Talk to product Read transform docs