Pravija AI consulting
ML · Deep learning · LLMs · Generative AI

AI that holds up after the demo.

Pravija helps teams take machine learning and generative AI from an idea to a system that runs in production, measured against the numbers your business already tracks.

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15+ years in data science and ML · Experience at Cisco and Yahoo · Masters in Machine Learning & AI

train loss val loss epoch 50 · early stop
Services

Where we help

Four practice areas, one approach: start from the decision the model supports, then pick the simplest technique that moves it.

Machine learning

Forecasting, scoring and classification models on your structured data, with the evaluation and monitoring to trust them.

classificationforecastingfeature engineeringSpark & AWS

Deep learning

Neural networks for images, text, audio and sequences, trained, tuned and compressed to run within your latency and cost budget.

NLPdocument intelligencetransformersmultimodal AI

LLM applications

Assistants, search and document workflows built on large language models, grounded in your own data and tested before they reach users.

RAG · hybrid searchrerankingRAGAS evalsagents & MCP

Generative AI

Fine-tuning open models on your data and generating synthetic training data, with fast, cost-aware inference.

LoRA / QLoRASFT & DPOsynthetic dataGPU inference
How we work

From question to production

Each stage ends with something you can evaluate, so you can stop, adjust or scale with real evidence.

  1. Discovery

    Map the problem, the data you have and the metric that defines success.

    1–2 weeks

  2. Prototype

    Build a working baseline and measure it on held-out data before anything is promised.

    2–4 weeks

  3. Production

    Harden the model into a service with monitoring, cost controls and fallbacks.

    4–8 weeks

  4. Handover

    Document, train your team and set up retraining so the system stays yours.

    ongoing
Typical projects

What clients ask for

A few of the problems these methods solve well.

Knowledge assistantAn internal chatbot that answers from your policies, manuals and tickets, with sources.
Document extractionPull fields from invoices, contracts or forms into structured data automatically.
Demand forecastingPredict sales or inventory needs weekly, with error bands your planners can use.
Agentic workflowsMulti-agent systems that plan, pick tools and run multi-step tasks inside your existing tools.
AI strategy reviewAn honest read on which AI ideas are worth building and which are not yet.
Model auditCheck an existing model for accuracy drift, bias and runaway inference cost.
About
Founder-led
One senior practitioner, start to finish

Pravija is led by a data scientist and ML engineer with more than 15 years of experience building analytics and machine learning systems on large datasets, from data ingestion and feature engineering to model training, evaluation and production integration.

Our founder's recent work covers agentic AI platforms with multi-agent orchestration and MCP, and an enterprise RAG platform over millions of documents. You work directly with the person building your system, from the first data review to the production rollout.

Contact

Have an AI problem worth solving?

Send a few lines about what you are trying to do and the data you have. You will get a reply within two working days.

hello@deepakmishra.ai