Open to selected freelance AI/ML projects
Currently working full-time as an AI/ML Engineer, and taking on a small number of freelance engagements alongside it - which means I am selective, and honest about timelines before we start.
Capacity
Part-time, limited engagements
Response time
Usually within 24 hours
I work with
Startups, Product teams, Research groups, Agencies
Services
What I can build for you
Every service listed here maps to something I have actually shipped — the note under each one says what backs it up.
Custom RAG Systems
Retrieval over your own documents, data or knowledge base - including the cases where naive chunk retrieval falls apart and the domain needs to be modeled as a graph.
- Ingestion & chunking pipeline
- Hybrid semantic + BM25 retrieval
- Graph RAG where relationships matter
- Retrieval evaluation harness
AI Agents & Agentic Workflows
Multi-agent systems that do real work against real tools - orchestrator/sub-agent architectures rather than one prompt asked to do everything.
- LangGraph / CrewAI orchestration
- Specialized sub-agents per concern
- Agent memory design
- Failure handling and retries
MCP Tool Servers & Integrations
Standardized tool access for your agents, so adding the next integration does not mean inventing another bespoke protocol.
- MCP servers (SSE and stdio)
- Tool schema design
- Database and API tool nodes
- Schema introspection for dynamic SQL
LLM Chatbots & Assistants
Assistants grounded in your content that answer from what you actually published, and say so when they do not know.
- Grounded question answering
- Conversation memory
- Fallback and refusal behavior
- Web or API delivery
Natural Language to SQL / Query
Let non-engineers ask your database questions in plain English, against the live schema rather than a stale snapshot.
- Schema introspection layer
- Query generation and validation
- Governance rules as agent context
- Result explanation
Guardrails & AI Safety Review
Input and output screening for systems that touch regulated or personal data - and a look at what your agent does when someone tries to talk it out of its instructions.
- Input / output guardrail layer
- PII / PHI screening
- Prompt-injection resistance
- Policy-aligned refusal behavior
LLM Evaluation Harnesses
A way to tell whether your last prompt change helped or hurt, instead of arguing about sample outputs.
- Labeled evaluation dataset
- LLM-as-judge scoring
- Faithfulness & relevancy metrics
- Regression tracking between iterations
Cost & Latency Optimization
Routing, caching and model-tier decisions for systems where the inference bill has started to matter.
- Query complexity routing
- Cost-tiered model dispatch
- Response caching
- Cost and routing dashboard
How it works
From first message to shipped work
Tell me what you are building
Send the problem, not the spec. What the system needs to do, who uses it, and what breaks today.
Scope call
A short call to pin down constraints, data access and what success actually looks like.
Proposal & timeline
A written scope with milestones and an honest timeline that accounts for my full-time commitments.
Build & iterate
Working increments you can see, with evaluation in place so quality is measured rather than asserted.
Project inquiry
Tell me what you are building
Send the problem, not the spec. I read every inquiry personally.
Prefer email?
Ksaikiran129@gmail.comWhat happens next
I reply within about a day — usually with a couple of questions before anything else. If it is not a fit, I will say so quickly rather than leave you waiting.