You will get LLM Agent for One Workflow

Name: You will get LLM Agent for One Workflow
Availability: InStock

Ananta P. Ananta P.

4.8

Top Rated

Ananta P. Ananta P.

4.8

Top Rated

Project details

I build one workflow properly rather than a platform badly.

Most agent projects fail the same way. They demo beautifully, go live, then fail quietly in ways nobody notices for weeks, because nothing was measuring them and nothing was logging why.

So the evaluation harness gets built alongside the agent, from day one rather than bolted on at the end. Every run is scored against cases we agree upfront. Every failure is logged with the full reasoning trace. When something goes wrong you can see which step broke and why, instead of re-running it and hoping.

The second thing I insist on is a human in front of anything irreversible. Before any code is written we list the actions the agent can take, the access level of each, and which ones require approval. That list is agreed in writing. An agent that can quietly post to your ledger is a liability, not a feature.

Scope stays deliberately narrow. One workflow, tightly defined, working reliably on Monday morning. Not a framework, not a platform, not an assistant that does everything adequately and nothing dependably.

In data engineering since 2012, so the integration side is not an afterthought.

AI Algorithms

Large Language Model, Transformer Model

AI Applications

AI Chatbot, AI Content Creation, AI Mobile App Development, AI-Enhanced Classification, AI-Generated Code, AIOps, Anomaly Detection, Conversational AI, Natural Language Generation, Natural Language Understanding, Sequence Modeling, Speech Synthesis

AI Development Language

Python

AI Models

BERT, ChatGPT, DALL-E, Dolly, LLaMA, Midjourney AI, Stable Diffusion, Whisper

What's included

Service Tiers	Starter $1,200	Standard $2,000	Advanced $3,200
Delivery Time	8 days	12 days	18 days
AI Model Integration			-
Batch Normalization	-	-	-
Database Integration
Detailed Code Comments	-
Image Upscaling	-	-	-
MLOps	-	-
Model Deployment	-	-
Model Documentation
Model Monitoring	-	-
Model Testing & Optimization	-		-
Model Tuning	-	-
Natural Language Processing
NLP Tokenization	-	-
Pre-Training	-	-	-
Prompt Engineering
Setup File
Source Code

Frequently asked questions

4.8

52 reviews

87% Complete

(45)

8% Complete

(4)

4% Complete

(2)

2% Complete

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1% Complete

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Apache Superset Integration Expert Needed

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.

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.

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.

Vehicle OBD GUI Development

About Ananta

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AI & Data Engineering | LLM Agents, Text-to-SQL, Data Pipelines

91% Job Success

4.8 (52 reviews)

Pune, India - 12:01 am local time

Most AI projects die between the demo and production. I close that gap: LLM agents, RAG,
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.

Workflow mapping

We map the workflow end to end and agree exactly where the agent stops and a human takes over.

Tool and guardrail design

I define the tools it gets, the access level of each, and the limit on every action. Agreed in writing before any code.

Review the work, release payment, and leave feedback to Ananta.

Select service tier

Starter$1,200

Standard$2,000

Advanced$3,200

Single Workflow

One single-tool agent for one workflow, with evals and failure logging.

Delivery Time 8 days
- AI Model Integration
- Database Integration
- Model Documentation
- Natural Language Processing
- Prompt Engineering
- Setup File
- Source Code

8 days delivery — Sep 1, 2026

Revisions may occur after this date.

Upwork Payment Protection

Fund the project upfront. Ananta gets paid once you are satisfied with the work.