Zatanna
Product & Competitive Intelligence
Turns legacy software workflows into agent-first APIs by observing human actions.
Company Overview
Turns legacy software workflows into agent-first APIs by observing human actions, reconstructing the underlying request flow, and exposing stable endpoints for AI agents and internal systems.
Competitive Advantage & Moat
Product Roadmap & Public Announcements
Publicly, Zatanna is focused on turning human-only workflows into reliable APIs for AI agents, with emphasis on session handling, auth, retries, request sequencing, proxies, TLS fingerprinting, and anti-bot resilience. The likely near-term roadmap is a more self-serve workflow capture product, deeper observability, reusable integration templates, and enterprise controls for sensitive environments.
Signals & Private Analysis
Private and non-traditional signals suggest the team started from vertical AI pain points and pivoted down the stack into infrastructure. Founder backgrounds and messaging point to strong anti-bot and workflow reverse-engineering capability. The absence of broad public hiring suggests a tight founder-led technical team, while customer/logo and throughput claims imply high-touch deployments with strong pressure toward productization. CEO Rithvik Vanga's background includes Coinbase, Series, Hamming AI, and John Deere with a University of Michigan CS degree.
Product Roadmap Priorities
Uses ML to infer the hidden structure of legacy software workflows from a demonstrated task and convert that behavior into a stable, agent-usable API.
Instead of making an AI click around a website forever, it learns the important steps once and turns them into a clean machine-readable action.
This is like watching someone navigate a chaotic government office once, then drawing a secret back-door map so everyone else can skip the waiting room forever.
Uses ML-assisted detection and adaptation to keep workflow-backed APIs reliable when upstream software changes, fails, or triggers anti-bot defenses.
When the old software changes or breaks, the system tries to figure out what went wrong and recover instead of just failing silently.
It is like having a mechanic riding inside the car who can tell whether the problem is bad gas, a dead battery, or a closed road, then reroute before the trip is ruined.
Uses ML to translate messy outputs from legacy systems into clean structured responses and agent-compatible tool interfaces.
It turns confusing screens and software responses into neat, standardized answers an AI agent can actually use.
It is like hiring a translator who not only speaks every messy software dialect, but rewrites each answer into the same clean memo format your whole team can use.
Company Overview
Key Team Members
- Rithvik Vanga, Co-Founder & CEO
- Alex Blackwell, Co-Founder & CTO
- Tarun Vedula, Co-Founder & COO
Founder Force Multiplier
Zatanna's edge is a combination of anti-bot know-how (Alex Blackwell previously at Pikkit bypassing anti-bots), workflow reverse engineering, and a thesis that the real bottleneck for agents is software access rather than model intelligence alone. Rithvik Vanga brings experience from Coinbase, Hamming AI, and John Deere (University of Michigan CS).
Funding History
- 2025 | Rithvik Vanga, Alex Blackwell, and Tarun Vedula co-found Zatanna.
- 2026 | Accepted into Y Combinator Winter 2026 batch.
- 2026 | Likely ~$500K raised to date (YC standard deal).
Competitors
- Browser Automation and RPA: UiPath, Automation Anywhere, Browserbase, Playwright-based agent tooling.
- API and Integration Tooling: Merge, Paragon, Finch, Pipedream.
- Agent Infrastructure and Computer-Use Startups: Harvey-style workflow tools, Operator-like agent layers, and stealth AI automation startups building request-layer abstractions.
