JarvisX
Google Cloud Partner

Legacy SQL, ETL & workflows —migrated with evidence and speed,not promises.

Upload your repo. Every artifact is rewritten, then scored across 13 fidelity-validation layers and flagged for review — before it ever hits production. Solo trials or team migrations, same platform.

Start a Quick RunCreate a WorkspaceAnalyze GitHub repoFreeLive SQL ValidatorNew

Quick Run for ad-hoc, pay-per-use migrations · Create a Workspace for team projects with review & add-ons.

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Common starting points:TeradataOracleInformaticaDataStageSSISTalend+ 16 more
Upload legacy repository
.sql · .bteq · .xml · .py · .json · .csv
parse
convert
validate
output
SOURCE · TERADATA
CREATE MULTISET VOLATILE
TABLE rank_tmp AS (
SEL dept_id, emp_id,
sal,
ROW_NUMBER() OVER (
PARTITION BY dept_id
ORDER BY sal DESC) AS rn
FROM emp QUALIFY rn = 1
) WITH DATA ON COMMIT
PRESERVE ROWS;
TARGET · BIGQUERY
CREATE OR REPLACE TEMP
TABLE rank_tmp AS
SELECT dept_id, emp_id,
sal
FROM (
SELECT *, ROW_NUMBER()
OVER(
PARTITION BY
dept_id ORDER BY
sal DESC) AS rn
FROM emp)
WHERE rn = 1;
Idle — Ready0%
Platform Pillars

Convert · Validate · De-risk

Three stages enterprises need from a code modernization platform.

Pillar 01

Convert

Automatically convert SQL, ETL, code, and schemas across modern cloud platforms — Teradata → BigQuery, Informatica → Airflow, Python → modern runtimes. Six specialized products under one roof.

JarvisQueryJarvisCodeJarvisFlowJarvisSchema
Pillar 02

Validate

Our 13-layer Quality Engine checks completeness, fidelity, syntax, repair, and confidence before output. Layer 11 even runs each converted query against generated sample data (in-process DuckDB) and diffs the result rows against the source — proving correctness, not just syntax, and self-repairing on failure. Every artifact is scored, not guessed.

13-Layer Quality Engine·Live Execution (DuckDB)·Auto-Repair
Pillar 03

De-risk

Understand database dependencies, column lineage, migration risk, and test data requirements before production cut-over. Ship with confidence — not with crossed fingers.

JarvisGraphJarvisRiskJarvisData
What is New

More than a raw converter

Four advanced modernization themes designed for enterprise scale.

GitHub-Native

Connect your repository, select dialects, and JarvisX will convert branches, enable per-file commentary, and open a PR back with the output.

Team Workspaces

Create dedicated environments, invite teammates with role-based policies, audit migration steps, and review transpiled scripts together.

13-Layer Transparency

No black-box transpilation. Track each script through AST compilation, OpenAI auto-repair validation, and visual semantic score cards.

Enterprise dillegence

SOC 2 alignment and SAML 2.0 SSO, with region-pinned GCS storage, bring-your-own-keys (CMEK) and custom LLM API endpoints available on Enterprise request.

FAQ

Frequently Asked Questions

Clear answers on how the platform handles enterprise modernization.

90%+
Fidelity Validation Pass Rate
91
Migration Conversion Pairs
100%
AST Semantic Equivalence
Zero
Data Retention Mode