Sistava

Data Pipelines & ETL

AI Data & Analytics Team

CSVs, APIs, and source systems → cleaned, joined, analysis-ready datasets

Your AI analytics team builds and runs the ETL no one wants to write — pulling from CSVs, APIs, databases, and SaaS sources, then cleaning, joining, and writing to a destination of your choice.,Pipelines are versioned. Re-runs are deterministic. Failures alert with the offending row and the proposed fix.,Outputs are analyst-ready: deduplicated, normalized, enriched, and joined to the entities you care about.

Benefits

How It Works

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At a Glance

Any
Source type supported
Versioned
Pipelines under change control
Deterministic
Re-runs produce same output
Alerting
On regression, not after

Pipelines That Do Not Drift

FAQ

Is this competing with Fivetran / dbt?

It works with them. Your team can write to dbt models or skip the stack entirely for lighter use cases.

How does it handle PII?

PII masking and field-level encryption supported. Configurable per source.

What about real-time pipelines?

Event-driven runs supported via webhook triggers and message queues.

Can it backfill historical data?

Yes — backfills are first-class with idempotency guarantees so you can re-run safely.