How we work
Deployment
Case Studies
Pricing
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Modernize from
Modernize SAS to
Deterministic parsers rewrite SAS to Databricks, Snowflake, BigQuery, and Python, and every output is checked row by row against the original. Run the software yourself, work alongside our engineers, or have us manage delivery.
No signup, no sales call: convert a real SAS job and read the output yourself. Budget estimates are on the pricing page.
Real SAS in, reviewable PySpark out — block by block. Open it →
Pick a target. We rewrite the workload for it — not SAS sitting on a cheaper server.
Need a different target? Tell us what you need →
Why this is different
Moving SAS onto a cloud VM, or wrapping DATA steps in Python, is the same job in a new costume. We rewrite the workload for the platform you actually want to run.
Used by data teams in
Millions of lines of production SAS, modernized and matched to the original before go-live.
Case Studies
Three production modernizations — what moved, how it was validated, and what it took.
4,200 SAS programs rewritten as native Databricks notebooks and PySpark in 18 months, validated to row-level parity.
Read the case study → 3,100 programsClinical SAS programs modernized to Snowflake SQL with audit-ready validation evidence for regulated data.
Read the case study → 1,900 scriptsSAS Enterprise Guide analytics moved to Google BigQuery — clinical outputs matched before go-live.
Read the case study →How It Works
Discover the estate. Rewrite it. Prove every row. Then go live.
Scan your SAS estate. Build inventory, lineage, and complexity scores.
Parser-driven translation to Databricks, Snowflake, BigQuery, or PySpark.
Row-level comparison proves outputs match. Data parity before go-live.
Ship to production with orchestration, monitoring, and audit-ready logs.
Walkthrough
Nine minutes, one production job, start to finish. Nothing sped up.
Recorded on an earlier build — the portal has since been redesigned. See the current one and convert a job yourself →
See It Work
Discovery, rewrite, validation, lineage, and docs — one platform, not a rehost.
Inventory, lineage, complexity scoring
Parser-driven translation to modern targets
Visual orchestration with centralized logs
Row-level parity proof before go-live
Context-aware assist in your environment. Every modernization runs without it.
Why SAS2PY
General-purpose LLM tools guess. SAS-compatible runtimes and vendor cloud moves keep you in SAS. Manual rewrite engagements run for years. SAS2PY parses your code with purpose-built compilers, then proves every row matches the original. AI is optional, never structural: turn it off and the modernization still runs end to end.
| Capability | SAS2PY | AI / LLM | WPS (World Programming) | SAS Viya | Professional Services Companies |
|---|---|---|---|---|---|
| Leaves SAS — not lift-and-shift | ✓ | ~ | ✗ | ✗ | ✓ |
| Deterministic parser (95%+ accuracy) | ✓ | ✗ | N/A | N/A | ✗ |
| Eliminates SAS license fees | ✓ | ✓ | Still pays WPS | Still pays SAS | ✓ |
| Row-level validation / data parity proof | ✓ | ✗ | N/A | N/A | ~ |
| Multi-target (Databricks, Snowflake, BigQuery, PySpark, Polars) | ✓ | ✗ | ✗ | SAS only | ~ |
| Self-service software (no consultants required) | ✓ | ✓ | ✓ | ✓ | ✗ |
| Column-level data lineage & STTM | ✓ | ✗ | ✗ | ✗ | ✗ |
| Full SAS coverage (Base, DI Studio, EG, Viya, macros, PROCs) | ✓ | ~ | ✓ | ✓ | ~ |
| Cost vs. manual rewrite | 60–85% less | Unvalidated | Still paying licenses | $$$$$ (SAS fees) | $$$$$ |
✓ Full support ~ Partial / limited ✗ Not supported N/A = Not a modernization tool
Deployment
Use the hosted SaaS portal at app.migryx.com with nothing to install, or deploy in your own environment — Docker, Kubernetes, OpenShift, or a Windows VM, up in under an hour. Self-hosted, your SAS code never leaves your network.
app.migryx.com — nothing to install, start modernizing from your browser. Request access →
One-command install on-premises or in your private cloud. No outbound connections, no external API calls — fully disconnected operation supported.
SSO (LDAP, Okta, SAML), role-based access, and full audit logs — there when your security team asks for them.
Engagement options
Choose how much delivery responsibility you want us to take. Every option uses the same SAS parsers and the same row-level validation; what changes is who runs the work.
Ranges on the pricing page are budget estimates. Final pricing and inclusions follow a scope and code review, and are set out in your proposal. Prefer proof first? Request a free assessment on a sample of your SAS →
No. Lift-and-shift puts SAS on a cheaper server, or wraps DATA steps in Python that still process one row at a time. We rewrite the workload as native Spark, SQL, and Python, then prove every row matches the original.
Deterministic parsers handle 95%+ of typical SAS code out of the box. Optional AI resolves ambiguous macros and undocumented logic, pushing accuracy higher. Every modernization ships with a validation report proving row-level parity.
Not unless you choose to. Self-hosted SAS2PY runs on-premises or in your own cloud — Docker, Kubernetes, or OpenShift, air-gapped capable — and your code never leaves your environment. Prefer zero setup? The SaaS portal at app.migryx.com runs the same engine in our secure cloud.
Partitioned validation compares row-level and aggregate outputs between legacy SAS and modern targets. Automatic schema checks, data matching reports, and exception trails provide audit-ready evidence.
Deployment itself takes under an hour. A readiness scan on estates from 100K to 100M lines runs 1–8 weeks, and a pilot on 10K lines takes about 2 weeks. Both are available under the Convert, Guided, and Full stack packages, run by your team or ours.
Not with Convert: it is software your team runs, with no services contract or RFP. If your team knows SAS but not the target platform, Guided adds six months of execution, remediation, and reconciliation support. With Full stack, our engineers manage delivery end to end and hand over documented, readable code.
Yes. Generated code ships documented and readable, with mapping sheets that tie every output back to the original SAS. Start with the SaaS portal or a guided pilot where we do the modernization, and your team ramps up on the target platform through training and handover.
Databricks notebooks, PySpark, Snowflake SQL, Snowpark, BigQuery, Polars, Fabric, Redshift, Cloudera, DBT models, and Python — with comments, mapping sheets, and auto-generated documentation.
Convert a real SAS job in the live converter with no signup and read the output yourself. Send a representative sample for a free assessment and we'll return modernized, validated output and a complexity report. Use the pricing page for a budget estimate across Convert, Guided, and Full stack, or request SaaS portal access. Questions: hello@migryx.com
Convert a SAS job right now, send us a sample for a free assessment, or read how an engagement runs stage by stage. Either way you see real modernized, validated output from your own SAS code before committing to anything.
Open the live converter, paste a real SAS job, and read the generated PySpark block by block. No signup, no sales call. Budget estimates for Convert, Guided, and Full stack are on the pricing page.
Try it yourself →Prefer proof on your own estate? Send a representative sample of your SAS code. We modernize it, validate the output, and return a complexity report at no cost.
Get a free assessment →Five stages, and you decide how far to go — discovery, proof of concept, pilot, first production wave, full estate. See who does the work, what we need from you, and where a demo, pricing, or deployment fits in.
How we work →
