Applied AI Consultant | LLMs · Agents · Memory Systems · Math

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Hi folks, thanks for dropping by! I'm Antaripa, 25 years young 🌸

I work as as an Applied AI consultant helping early-stage startups and companies build AI-native products. I work at the intersection of LLMs, agent frameworks, memory systems, and retrieval + eval pipelines.

Companies/Clients I have worked with as consultant:

• Mem0 (https://mem0.ai/**):** Implemented memory architectures for LLM agents, building real-world use cases, and wrote technical deep-dives on agent memory.
• Tavily (https://www.tavily.com/**):** Work on search and agents.
• Tensorlake (https://www.tensorlake.ai/**):** Contributed to core product engineering: helped building fast, scalable pipelines for end-to-end data processing in collaboration with their team.
• Agno (https://docs.agno.com/introduction): Built different agent use cases and tool integrations support with Agno.
• Sagacious → Designed and delivered a custom end-to-end search and retrieval system tailored for niche telecom domain along with building dataset and evals for them.
• Grappus (https://www.grappus.com/**) →** Designing and implementing ML pipelines and agentic workflows. Leading initiatives across multi-agent architecture and backend systems.
• LuppaAI (https://luppa.ai/**)** → Building the evals framework for automated content generation for brands.

Previously led NLP and search teams at:

• SproutsAI: Built and scaled candidate autosourcing and candidate scoring and recommendation system across jobs on 100M+ profiles. Tuned custom embedding models for performance.
• Cimba.ai: Created end-to-end ML pipeline for automating data analytics (text-to-SQL and text-to-python pipelines, semantic caching, benchmarking).

About Me 🌵

I have been working in the Machine Learning field for 3.5 years now. I love building things that work and learning how to make them better.

I enjoy working on: