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About Guru
AI/ML engineer and software developer with 1+ year of professional experience building LLM applications, RAG and agentic workflows, voice AI and healthcare AI systems. At Amrita Vishwa Vidyapeetham I built MedSum, a multilingual medical voice platform (STT, diarization, translation, medical NER, LLM extraction) that turns doctor-patient conversations into SOAP notes, piloted at Amrita Hospital Faridabad and Kochi, and ASHA, a multilingual mental-health conversational AI with an agentic LLM, RAG, safety controls and LangGraph-based evaluation, piloted with 248 participants. Skilled in Python, FastAPI, LangGraph, vector search, LLM evaluation, PostgreSQL, Redis, Docker and GCP. Author of five peer-reviewed publications.
Professional profile
- Location
- Bangalore, India
- Time zone
- Asia/Calcutta
- Work mode
- Remote, Hybrid, On-site
- Availability
- Available for Permanent Roles
- AI experience
- 1+ years
- Industry experience
- 1+ years
- Languages
- English, Telugu, Hindi
- Working hours
- 10:00–18:00 IST, Mon–Fri
- Typical response
- Within 24 hours
- Preferred engagement
- Small (individual or single team)
- Travel
- Occasional travel
- Available in
- India
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Proven on the network
Implementation records and publicly available work, where published.
0 AI Deployments delivered. No publicly identified implementations are available to inspect.
03
What Guru builds
Implementation domains listed on this profile. Evidence-supported items are identified separately below.
Specialisations
AI Agents
AI Evaluation & Testing
Conversational AI
RAG & Knowledge Retrieval
Voice AI
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AI Deployments
Real AI implementations demonstrated through evidence.
No publicly identified Deployments are available to inspect.
05
Implementation capabilities
Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.
Evidence-supported
No published evidence linked yet.
Builder declared
- AI Agents
- AI Evaluation & Testing
- Conversational AI
- RAG & Knowledge Retrieval
- Voice AI
06
Technology
Technologies listed by the Builder, distinguished by published evidence.
Evidence-supported
No published evidence linked yet.
Builder declared
- Chroma
- Django
- Docker
- FAISS
- FastAPI
- Flask
- Google Cloud
- Hugging Face Transformers
- LangChain
- LangGraph
- LangSmith
- LiveKit Agents
- MongoDB
- OpenAI Platform
- OpenAI Whisper
- Pinecone
- PostgreSQL
- PyTorch
- Python
- Redis
- TensorFlow
- pgvector
07
Industry experience
Published Deployments support the listed counts. Other industries are Builder declared.
Agriculture
Builder declared
Education
Builder declared
Healthcare Providers
Builder declared
Research
Builder declared
08
Trust & verification
A closer look at how this profile and its evidence are reviewed.
Community Member
Published evidence is reviewed against the AI Deploy Network Evidence Standard.
How verification works
Verified Builder
Independently reviewed by AI Deploy Labs against the platform Evidence Standard.
How this is verifiedWhat the platform has established, and what remains builder-declared.
- Identity and organisation
- Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
- AI Deployments
- An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
- Business outcomes
- Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
- Evidence
- Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
- Currency
- Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
- Traceability
- Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.
The platform does not independently audit client systems or financial records. How this is verified
Professional record and further evidence
Professional Certifications
Some recognitionClaude Code 101
Anthropic (Claude Academy)
Issued Oct 2026
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