JarvisX Documentation

JarvisX is an AI-powered code modernization platform built for enterprise migrations. It automatically translates legacy database views, stored procedures, analytical queries, ETL pipelines, and scripts into modern target-native dialects with semantic parity checks. Unlike simple LLM wrappers, JarvisX employs a strict 13-layer quality engine combining deterministic parsing with context-isolated LLM micro-prompts.

1. Sign In: Connect securely via Google SSO or magic-link fallback. Your personal organization is auto-minted immediately. 2. Choose Dialect Target: Specify your legacy source (e.g. Teradata, Oracle, Informatica) and target cloud (BigQuery, Snowflake, Databricks). 3. Upload Source: ZIP your directories or authorize the JarvisX GitHub App to select active repositories. 4. Quality Inspection: Run the 13-layer pipeline to generate AST syntax, semantic matching scores, and human-in-the-loop review flags. 5. Download: Close the tab; we will email you when the compilation is ready, or merge the output Pull Request directly on GitHub.

The Migration Readiness Analyzer (gojarvisx.ai/analyze) scans any public GitHub repository and returns a readiness report — file breakdown, dialect detection, risk findings, and a plan recommendation. Sign-in is required. Free repository scans are capped per account across your tenure: Free plan = 20 successful scans, paid plans (Starter / Growth / Scale) = 100 scans, Enterprise = 500 scans. Only scans that produce an actual report count toward the limit (failed or invalid-URL attempts do not). When you reach the cap, upgrade your plan to raise it. Your live remaining/total scan counter is shown right on the Analyze page.

An Organization is your team container for bills, logs, SSO, and workspaces. You do not need to create one manually — your personal organization is created automatically on your first action. Workspaces are isolated migration projects linked to a specific code repository (you can attach multiple ad-hoc batches and GitHub-imported codebases to one workspace). Submissions are lightweight one-off tries (like pastures on Try Now or ad-hoc batch ZIPs) that do not generate invoice templates. Collaborative roles include Owner, Admin, Reviewer, Member, and Viewer.

Layer 00: sqlglot deterministic transpilation (16 dialects). Layer 01: Pre-LLM deterministic rewrites (20 rules including NVL, QUALIFY, SEL expansion). Layer 02: Complexity-adaptive prompting. Layer 03: Feature detection cards. Layer 04: 91 pair-specific conversion cards. Layer 05: RAG HyDE + RRF reranking vector search. Layer 06: Advanced LLM agent translation. Layer 07: Post-LLM deterministic updates. Layer 08-09: Syntax & category validations. Layer 10: Auto-repair single-pass execution fixes. Layer 11: Sample semantic scoring. Layer 12: Confidence scoring and audit triggers.

Generate personal access tokens from the API Tokens panel. These tokens are hashed at rest. Use the JarvisX CLI to trigger batch migrations from your CI/CD pipelines.

curl -X POST https://gojarvisx.ai/api/v1/batch \
  -H "Authorization: Bearer <your_token>" \
  -F "file=@workload.zip" \
  -F "source_dialect=teradata" \
  -F "target_dialect=bigquery"

JarvisX is aligned to SOC 2 Trust Services Criteria. Data at rest is encrypted via AES-256 (CMEK keys available for Enterprise). TLS 1.3 is enforced globally with HSTS preloading. GCS buckets are regional (hosted in US; EU region-pinning available on Enterprise request). We support self-serve GDPR data deletion/export and offer a 72-hour breach notification SLA.