You will get AI & Data Readiness Assessment
Top Rated
Project details
Most AI consultants sell you the build. I check first whether your data can carry it, and I will tell you plainly when the answer is no.
That honesty is the product. I have been in data since 2012, and the pattern barely varies: the model was never the problem. The data was incomplete, undocumented, owned by nobody, or spread across systems that disagree with each other. Almost nobody checks that before the budget is committed, and the project dies six months later with nothing to show for it.
This checks it in a week. I go through your actual sources rather than a questionnaire, and score every use case you are considering on three things: whether the data exists to support it, what it would cost to build, and what it is worth to you. Some come back as build-now. Some need foundations first. Some are not worth attempting, and I say so.
What makes this different from a consultancy discovery deck is that I build the pipelines and the AI myself, so the effort estimates come from the person who would have to do the work. The document is vendor-neutral and it is yours. Clients have used it to brief other suppliers, which is fine by me.
That honesty is the product. I have been in data since 2012, and the pattern barely varies: the model was never the problem. The data was incomplete, undocumented, owned by nobody, or spread across systems that disagree with each other. Almost nobody checks that before the budget is committed, and the project dies six months later with nothing to show for it.
This checks it in a week. I go through your actual sources rather than a questionnaire, and score every use case you are considering on three things: whether the data exists to support it, what it would cost to build, and what it is worth to you. Some come back as build-now. Some need foundations first. Some are not worth attempting, and I say so.
What makes this different from a consultancy discovery deck is that I build the pipelines and the AI myself, so the effort estimates come from the person who would have to do the work. The document is vendor-neutral and it is yours. Clients have used it to brief other suppliers, which is fine by me.
AI Development Type
Knowledge RepresentationAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$600
|
Standard
$1,200
|
Advanced
$2,400
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 70 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
Frequently asked questions
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MN
Mahesh N.
Oct 17, 2025
Apache Superset Integration Expert Needed
EK
Emir K.
Jul 9, 2025
ETL Process and Preset Visualizations
Ananta was a true partner to our business—self-directed, reliable, and highly effective. Ananta is easy to collaborate with and he led our ETL development in AWS and built clear, impactful visualizations in Preset/Superset that directly supported key decisions. He understands business needs quickly, works independently, and consistently delivers high-quality work. He is a pleasure to work with—we are looking to use him again and we highly recommend him.
MR
Michael R.
May 30, 2025
Apache Superset Waterfall Chart enhancements
Ananta has been excellent to work with. We went above and beyond on our project and in an excellent communicator. He executed our Apache Superset improvements successfully, and he was thorough and timely in creation of PRs. 100% recommend.
RR
Raj R.
May 29, 2025
Data analyst & data visualization expert to create reports and configure Apache Superset
Working with Ananta was instrumental in transforming our data and product capabilities. They brought a rare combination of analytics expertise, ML proficiency, and a deep understanding of blockchain technologies, which significantly accelerated our product roadmap. Ananta quickly identified bottlenecks in our existing workflows and implemented solutions that improved team efficiency, fostered better collaboration, and made our data processes more reliable and scalable. One of their standout contributions was reviving our data product — refining the architecture, unlocking valuable insights, and aligning it more closely with business goals. Their hands-on approach, technical depth, and ability to work across disciplines helped bridge the gap between data science, engineering, and product development. We saw a marked improvement not just in output but in team morale and momentum. Ananta’s contribution has had a lasting positive impact on our operations, and we highly recommend them for any data-driven or blockchain-centric initiatives.
EY
Emrah Y.
May 29, 2025
Vehicle OBD GUI Development
About Ananta
AI & Data Engineering | LLM Agents, Text-to-SQL, Data Pipelines
91%
Job Success
Pune, India - 8:18 am local time
text-to-SQL, and the data pipelines and warehouses underneath them. 70 contracts, 1000+ hours, Top Rated.
Working in data since 2012. MTech in Data Science from BITS Pilani. 8 years at Accenture,
4 at Persistent Systems.
Most AI projects stall in the same place. The demo works, then it meets real data. That
gap is where I spend my time: ingestion, modelling, evaluation, and the unglamorous
reliability work that decides whether an agent survives contact with production.
WHAT I BUILD
AI and LLM systems
- LLM agents and multi-agent workflows, with tool use, retrieval and evaluation harnesses
- Text-to-SQL over real warehouses, with guardrails so business users can self-serve
- RAG pipelines: chunking, embeddings, retrieval quality, hallucination control
- AI features embedded into existing products, not standalone demos
Data engineering
- ETL and ELT pipelines from source systems into the warehouse
- Data quality, validation and pipeline observability
- Warehouse and lakehouse modelling
- Platform migrations and modernization
Analytics people actually use
- Apache Superset and Preset, across multiple long-running engagements including 100+ hour
front-end builds
- Executive dashboards, embedded analytics, custom visualizations
- Reporting layers that keep working after handover
RECENT WORK
- Text-to-SQL interface that lets executives query the warehouse in plain English
- ESG data ingestion and automation for compliance reporting
- Predictive maintenance models for manufacturing
- Superset front-end and visualization work across several repeat clients
STACK
Python, SQL, Claude and OpenAI APIs, LangChain, FastAPI, PostgreSQL, MySQL, Apache Superset,
Apache NiFi, Airflow, Elasticsearch, Power BI, AWS, Docker
HOW I WORK
Small scope first. I would rather prove the approach on a paid discovery or one narrow slice
than write a long proposal for something neither of us has tested. You get working code,
documentation and a real handover, not a dependency on me.
Good fit if you have real data, a real business problem, and you want something running
rather than a prototype.
Not a fit if you need someone to fill a seat and work a ticket queue.
Tell me what you are building and where it is stuck. I will tell you honestly whether I am
the right person for it.
Steps for completing your project
After purchasing the project, send requirements so Ananta can start the project.
Delivery time starts when Ananta receives requirements from you.
Ananta works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff call - 90 minutes
We walk through your systems together: what data exists, where it lives, who owns it, and what you want AI to do with it.
Data inventory
I assess every source or sample you shared for volume, quality, completeness and ownership, and record what is missing.