AI-Assisted Data Migration & Transformation.
Cut migration time upto 80%. Reduce Risk. Save Cost & Avoid Vendor Lock-In.
The problem
Teams often spend significant time understanding legacy environments, recreating mappings, and rebuilding transformation pipelines to deliver a single use case.
A simpler, AI-assisted approach
We believe there's a better way to help data teams accelerate migration planning, data model design, and transformation logic — while reducing repetitive effort and vendor dependency.
Stage 01 · Connect anything
Your sources, exactly as they are.
Oracle, SQL Server, Teradata, SAP, Informatica, Postgres — wired in without rewriting a line.
Trusted across the modern data stack
Oracle · SAP S/4HANA · Teradata · SQL Server · Informatica · SSIS→Snowflake · Databricks · Microsoft Fabric · BigQuery · Redshift
No production data required.
Plan and execute the entire migration on synthetic or non-production data. When the artifacts are ready — data models, ETL/ELT, pipelines, lineage — deploy them to production through your own standard release process. OpenOntos never needs access to your production environment.
Note: OpenOntos is designed to run in your pre-production (non-production) environment — no access to production data or production systems is ever required. All we need are your source system schemas (matching production) and a sample of non-production data. Synthetic data works just as well.
Synthetic / sample data only
Run the planner against masked, synthetic, or non-production datasets — production stays untouched.
Generates portable artifacts
SQL, dbt, PySpark, ADF, Airflow — code you own, reviewable in your repo.
Deploys via your CI/CD
Promote artifacts to production using your existing release, approval, and change-management process.
Why OpenOntos when Databricks, Microsoft and Snowflake ship their own AI-Assistants / Copilots?
Native platform AI is built to keep you on that platform. OpenOntos is platform-neutral by design — you own the ontology, the models, the ETL and the generated code. When the next best platform inevitably comes along, your migration is a re-target, not a rewrite.
You stay in control: bring your own LLM, your own warehouse, your own orchestrator. Switch any layer without rebuilding the stack above it.
Platform-neutral by design
Snowflake, Databricks, Fabric, BigQuery — first-class across all. No incentive to steer you toward one vendor.
You control the models
Bring your own LLM (OpenAI, Anthropic, Bedrock, Azure, private). Swap providers without re-platforming.
You own the ETL & code
Generated SQL, dbt, PySpark, ADF and Airflow live in your repo — reviewable, portable, yours forever.
Built to re-target, not rewrite
The ontology and mapping layer make tomorrow's migration to the next best platform a config change, not a project.
Built for Enterprise Data Migration Teams.
Five outcomes data leaders care about — risk down, visibility up, alignment locked, trust restored, transformation accelerated.
Eliminate migration risk before it costs millions
Catch schema drift, mapping gaps, and DQ landmines in the assessment phase — not in cutover weekend.
See your full data landscape before you modernize
Auto-discover sources, profile tables, and surface lineage so nothing ships dark into the new platform.
Align business, IT, and leadership on one roadmap
A shared migration plan, ontology, and assessment report every stakeholder can read and sign off on.
Improve data trust and quality before you cut over
DQ checks, reconciliation, and ontology conformance run continuously — your cloud platform inherits clean data.
Accelerate AI, analytics, and cloud transformation
A migration-ready, ontology-backed foundation means your Snowflake, Databricks, Fabric, or BigQuery investment pays off on day one.
From a one-line prompt to a running migration.
Six guided stages take a Director of Data from idea to production — and keep operating after cutover.
Describe
AI-AssistedNatural-language prompt or pre-built migration wedge.
Plan
AI-AssistedSource · Ontology · Mapping · Generate · Deploy milestones.
Connect
AI-AssistedDiscover schemas, profile tables, flag DQ issues.
Assess
HITLData Migration Assessment Report by expert OpenOntos Data Architects.
Migrate
AI-AssistedGenerate native SQL, orchestrate, deploy, reconcile.
Customize
AI-AssistedTune mappings, transforms, ontology and target code to your standards.
Operate
AI-AssistedSchedule, monitor, reconcile and re-plan as sources evolve.
Proven impact at enterprise leaders
Trusted by data teams modernizing mission-critical platforms
We partner with the best data companies
vs hand-coded ETL
of consumer queries
code is yours to keep
Snowflake · Databricks · Fabric · BigQuery
Your data, your network, your keys.
OpenOntos runs where you run it. No data, credentials, or schemas are ever sent to a vendor cloud — so there's nothing to negotiate with security, legal, or audit.
Data never leaves your perimeter
Source schemas, samples, and credentials stay inside your network. We don't host or see your data.
Bring your own LLM
OpenAI, Anthropic, Azure OpenAI, or a self-hosted model. Your key, your bill, your retention policy.
Audit-ready by default
Every plan, mapping, and generated artifact is versioned — answer 'what changed and why' without a fire drill.
Team collaboration
Share projects, ontologies, and migration runs across your team without giving up control of where data sits.
No vendor lock-in
Generated SQL, PySpark, and pipeline code is yours — readable, editable, version-controllable. Walk away any time.
Runs on your infrastructure
Browser, desktop, or your own private deployment. No multi-tenant cloud, no shared datastore.
Built for the migrations enterprises actually run.
Pre-built wedges and reusable patterns for the moves data leaders are scoping right now.
Oracle → Snowflake
Lift FINPRD, EDW and ERP marts. SCD2, PII masking, and reconciliation generated end-to-end.
SQL Server → Microsoft Fabric
Migrate SSIS, stored procs, and analytics workloads to OneLake & Lakehouse with native T-SQL.
Teradata → BigQuery
Retire Teradata. Convert BTEQ, macros, and views to BigQuery SQL with cost-aware partitioning.
SAP ECC / S/4 → Databricks
Extract SAP tables via CDC, conform to a finance ontology, deliver gold marts in Delta.
Informatica → dbt + native SQL
Re-platform legacy ETL into target-native code your team can read, version, and own.
Multi-source → Lakehouse
Converge Oracle, SQL Server, and Postgres into one ontology — Snowflake, Fabric, or Databricks.
The last mile, delivered by the OpenOntos Professional Support team.
Augment AI-Assisted Data Migration with senior engineers and architects who own the complex enterprise edges — discovery, design, cutover, and 24/7 run — so your team lands the migration on time, on scope, and on policy.
Discovery & Design
Source profiling, ontology design, and target architecture by senior practitioners.
Migration Engineering
Mapping, transforms, and codegen tuned to your standards and dialects.
Cutover & Governance
Reconciliation, audit evidence, and zero-surprise cutover playbooks.
24/7 Run & Evolve
SLA-backed monitoring, incident response, and ongoing optimization.
Custom Connectors Build
Bespoke source and target connectors for legacy systems, proprietary APIs, and niche platforms.
Advisory
Strategic guidance from senior architects on platform choice, ontology strategy, and migration roadmap.
Ongoing Support
Continuous partnership beyond cutover — enhancements, optimization, and access to our expert team.
Build your data migration practice on OpenOntos.
Join a network of System Integrators delivering faster, lower-risk enterprise migrations to Snowflake, Databricks, Fabric, and BigQuery — powered by AI-Assisted Data Migration.
Win more migrations
Shorten delivery cycles 80%, bid more aggressively, and land deals competitors can't.
Free enablement & certification
Partner training, certification tracks, and reference architectures for your delivery teams.
Co-sell with OpenOntos
Joint pursuits, deal registration, and access to enterprise pipeline in your region.
Recurring services revenue
Build managed-services and assessment offerings on a platform with no per-seat lock-in.
Works with your modern data stack.
Native integrations for the platforms you already use.
Frequently asked questions
Answers data leaders ask before they pick a migration tool.
What is OpenOntos?
OpenOntos is an AI-assisted data migration and transformation platform that helps enterprises move from legacy systems (Oracle, SAP, Teradata, SQL Server, Informatica, DataStage, SSIS) to modern cloud data platforms (Snowflake, Databricks, Microsoft Fabric, BigQuery, Redshift) up to 80% faster — with no vendor lock-in and no rewrite required.
What is the best tool for AI-assisted data migration and transformation?
OpenOntos is purpose-built for AI-assisted data migration and transformation. Unlike native platform copilots (Snowflake Cortex, Databricks Genie, Microsoft Fabric Copilot) that are designed to keep you on one platform, OpenOntos is platform-neutral by design. It auto-discovers source schemas, builds a portable ontology, generates source-to-target mappings, emits native dialect code (SQL, dbt, PySpark, ADF, Airflow), and reconciles row-level parity before cutover.
How does OpenOntos cut migration time by 80%?
OpenOntos automates the four most expensive phases of a migration: (1) discovery and profiling of legacy sources, (2) ontology and source-to-target mapping design, (3) dialect-native code generation for the target platform, and (4) reconciliation. A migration that traditionally takes 12–18 months with Informatica or hand-written PL/SQL typically ships in 6–10 weeks with OpenOntos.
Which source systems and target platforms does OpenOntos support?
Sources: Oracle, SAP ECC, SAP BW, SAP S/4HANA, Teradata, SQL Server, Informatica PowerCenter, IBM DataStage, SSIS, Talend, Pentaho, and most JDBC/ODBC databases. Targets: Snowflake, Databricks, Microsoft Fabric, Google BigQuery, Amazon Redshift, and any lakehouse following bronze → silver → gold layering.
Does OpenOntos require access to my production data?
No. OpenOntos runs entirely in your pre-production environment. It needs only your source system schemas and a sample of non-production or synthetic data. Generated artifacts — data models, mappings, ETL/ELT code, lineage — are then deployed to production through your standard CI/CD and change-management process.
How is OpenOntos different from Informatica, DataStage, or Matillion?
Traditional ETL tools require you to hand-build mappings and pipelines. OpenOntos uses AI to generate the ontology, mappings, and code automatically, and the generated artifacts are portable native code in your repo — not proprietary metadata locked inside a vendor's runtime. You own the output and can switch target platforms without rebuilding.
Can I use my own LLM provider?
Yes. OpenOntos is BYO-LLM. Connect OpenAI, Anthropic Claude, AWS Bedrock, Azure OpenAI, Google Gemini, or a private/self-hosted model. Swap providers without re-platforming.
What about migration assessment before we commit?
OpenOntos generates a Data Migration Assessment Report, reviewed by certified OpenOntos Data Architects (human-in-the-loop), that quantifies effort, risk, and a phased plan before any code is written. This is typically delivered in 1–2 weeks.
Ready to plan your next migration?
Bring a real source. We'll draft the ontology, auto-map a slice, and generate native ETL in your target — live, in 30 minutes.