Tavi
Engineering standups are supposed to unblock people. In practice, every small question becomes a follow up: “what does that endpoint return?”, “can someone draft the ticket?”, “let’s just bump that timeout.” A team walks out with 15 tiny action items on top of the real work, and each one costs a context switch, a Slack thread, or another meeting. We’re building Tavi to clear those small items during the standup itself, so people only leave with the big tasks they own.
Tavi joins the standup as a voice teammate. When someone asks a question about the codebase, Tavi answers it on the spot. When someone needs a ticket, PR description, or summary, Tavi drafts it while everyone is still talking. When the team agrees on a small change, a sandboxed coding agent makes it and shows the result in a live preview before the meeting ends. The hard part is that standups are several people talking to each other, not to an assistant. Tavi has to tell when it’s being asked something, when a comment follows up on its last answer, and when to stay quiet. We test that by playing scripted multi person meetings into it with synthetic voices and scoring when it spoke and when it should have.
For startups and founding teams
Karthik Thyagarajan is a founder-engineer studying Computer Science and Artificial Intelligence at Purdue. At Samsung Research America, he co-architected an always-on AI agent runtime for XR glasses. He is currently building Tavi, a voice teammate for engineering standups, and co-founded buildpurdue, a founder community at Purdue. His work spans agent infrastructure, on-device AI, product engineering, and evaluation.
For an early team building AI products, his strongest demonstrated fit is owning a broad technical problem from product decisions through implementation and evaluation. His current interests are live voice and video AI, AI-first wearables, and infrastructure that lets agents discover and use internet services.
Substantial ownership of agent systems
At Samsung Research America (May to August 2026), he co-architected an always-on agent orchestrator in Kotlin and owned half of a 25+ module runtime. His reported on-device router achieved 95% signal suppression and 90% intent-routing accuracy. His work also covered tool permissions, model routing, memory, and phone control, connecting model behavior to a usable device experience.
Builds teams and operating systems around a problem
As buildpurdue's co-founder and co-president, he helped turn an informal gathering into a founder community with a selective cohort, weekly co-working, funding, and founder-led problem-solving workshops. He built much of its web platform and integrated CRM, applications, events, and check-ins. His account describes data on around 500 students and a mailing list of about 1,000.
Makes technical claims testable
He built PARM, an open-source causal benchmark for when an agent should use personal memory: 157 frozen scenarios and 471 executable cases, with deterministic scoring and versioned replay artifacts. Its portfolio account explicitly distinguishes development results from held-out claims. He also built google-tools-mcp, a published MCP server exposing 169 Google Workspace tools through one OAuth flow.
Pursues difficult product problems
He is currently building Tavi, a voice teammate intended to answer codebase questions and handle small action items during engineering standups. The project tackles multi-person turn-taking, when to stay quiet, sandboxed coding, and synthetic meeting evaluations. This is ongoing work, rather than a claim of shipped adoption. His published interests explain the direction behind it.
Co-founder who ships and thinks about distribution
At Repple (November 2025 to June 2026), he co-founded a competitive fitness app released on the App Store and built the entire FastAPI, PostgreSQL, and Supabase backend, including synchronized workouts, ELO matchmaking, and weekly competition logic. His firsthand account also describes marketing before the UI existed, campus distribution, and why local community density mattered to the product.
This brief summarizes Karthik's public portfolio and firsthand accounts. Employment contributions and internal performance metrics are self-reported; linked code and artifacts provide additional evidence where available.