01
Outcomes, not software
You hire us for a result. OpenOntos comes with it, complimentary. You never pay a license to find out whether the tool works.
Enterprise Data & AI Consulting
Data Platform Modernization and AI-readiness are sold as two projects. They’re one.
The semantic layer your agents need is a byproduct of migrating your data properly. Lucid does both in a single engagement, brings the accelerator at no extra cost, and hands you code you own.
Migrate toMicrosoft FabricDatabricksSnowflakeAWSGCP
The stance
We are a consultancy, not a software vendor. What you buy is the outcome: a modernized data platform, a grounded knowledge layer, and agents your business can trust. When our OpenOntos accelerators fit your situation, we bring them at no extra cost to get you there faster.
Why one engagement, not two
Most firms bill modernization and AI-readiness as two year-long projects.
They’re one project. When you profile a legacy schema and map the fields and constraints properly, you’ve already produced most of the ontology your agents need. Most migrations throw that away the day after cutover. We keep it. You get cloud-native code and a grounded knowledge layer from a single engagement.
- Legacy estateAI ambitions
- One
engagement - Cloud-native code you ownGrounded semantic layer
Why Lucid
A senior team with an engine the big firms don’t have.
02
The accelerator does the repetitive 80%
Profiling, ETL dialect conversion (BTEQ, PL/SQL, stored procs to dbt and PySpark), pipeline generation, ontology drafting. Our people spend their time on the 20% that needs judgment.
03
You own what we build
Plain SQL, dbt, PySpark, ADF and Airflow, living in your repo. Open standards for the knowledge layer. Portable, reviewable, yours forever.
04
One motion, two outcomes
The migration produces the ontology. Cloud-native code and a grounded knowledge layer together, not two consecutive projects.
05
Agents and dashboards that agree
We close the knowledge gap that makes agents hallucinate and the definition gap that makes every dashboard disagree, with one semantic layer read the same way across tools.
How the work is shaped
Assess. Modernize. Ground. Run.
- 01
Assess
A fixed-fee migration and AI-readiness assessment. We profile what you actually have, surface the DQ landmines and undocumented procs before they blow up a cutover, and tell you what your agents will and won't be able to do. You get a report and a plan whether or not you hire us for the build.
- 02
Modernize
Lift and shift, or redesign into a modern lakehouse architecture. We move the estate to cloud-native code you own, on Microsoft Fabric, Databricks, Snowflake, AWS, or GCP. ETL dialect conversion, profiling, pipelines. Fixed scope, weeks not quarters.
- 03
Ground
We turn the migration byproduct into a real, standards-based semantic layer and deploy agents grounded in your certified data.
- 04
Run
Optional managed service once it's live, watching the pipelines and the agents in production. It's a service, not a license. Cancel anytime.
Open standards, no lock-in
Built to standards you can leave with.
Your code lives in your repo. The knowledge layer is built to open standards: W3C ontologies (OWL, SKOS, SHACL), and aligned to the Open Semantic Interchange, the vendor-neutral semantic standard backed by Snowflake, Google, AWS, dbt and others. One definition of revenue, read the same way by your BI tools and your agents, on any platform.
Standards
- dbt
- PySpark
- OWL
- SKOS
- SHACL
- OSI-aligned
Platforms
- Microsoft Fabric
- Databricks
- Snowflake
- AWS
- GCP
OSI is a young standard, finalized in early 2026. We build to it because vendor-neutral is the right long bet, and we’ll tell you where it’s mature and where it isn’t.
ontology/revenue.yaml
1concept: Revenue2definition: Net amount invoiced to a customer.3aligned_to: osi.metric.revenue4source:5model: models/revenue.sql6grain: customer_id7measures:8- name: revenue9expression: sum(net_amount)10unit: currency11governance:12owner: finance.analytics13certified: true
one definition. read the same way by BI and agents.
What we don’t do
The fastest way to trust us is to hear where we stop.
We don't sell software licenses.
The accelerators come with the engagement.
We don't rescue migrations with zero source documentation and no one who understands the legacy system.
That's an archaeology project, and we're not the first call.
We don't do staff augmentation.
You can't rent our people by the month to sit in your standups.
We don't replace your catalog or governance tool.
We make Purview, Unity Catalog, and Collibra useful faster.
We don't lock you into a runtime you have to keep paying for.
Open standards, your repo, your cloud account.
We don't leave your team dependent on us.
Every engagement transfers the knowledge and the tools to run, extend, and own what we build, so your people are fluent in the modern data and AI stack after we go.
Trusted by enterprise data teams
- Many
- named enterprise case studies
- $500K+
- annual savings, Heritage Grocers Group
- 60–90 days
- typical delivery, not quarters
- 80%
- migration time reduction with OpenOntos
Real migrations, measured in weeks, dollars, and reporting latency.
Who you're working with
Founder-led. Industry Trusted Data & AI Advisor
Lucid is led by Venu Amancha, who has spent his career inside enterprise data engineering and migration. The work is done by senior practitioners, not a bench of juniors on a clock.
We built OpenOntos because we were tired of watching migrations take 14 months and finish with the wrong data in the right place. The accelerator does the repetitive work so the senior team can spend its time on the parts that actually need judgment.
Featured
Venu on FabconTV, on building enterprise AI agents.
Start with an assessment
Tell us what you're migrating off.
A fixed-fee assessment gives you a profile of your real data, the risks before cutover, and a plan. You keep the report whether or not you hire us for the build.