One AI employee for 120,000 companies

Okara presents itself as an AI CMO: give it a website URL and it builds a marketing strategy, develops a brand voice, and dispatches specialized sub-agents across SEO, content, and social channels. The company behind it runs lean by design. Four people operate the platform, which processes 4 billion tokens daily and handles growth for more than 120,000 businesses.

The product routes work through eight sub-agents covering SEO, GEO, social, content, Reddit, and Hacker News. Founder Fatima Rizwan argues that distribution remains stuck in a pre-AI model, fragmented across subscriptions and agencies that can cost over $15,000 a month before generating any return. "You can build something in a weekend and spend months trying to get anyone to notice," she says. For zero founders, the pitch is straightforward: agency-level distribution muscle without the headcount or the monthly bill.

"We're four people building for hundreds of thousands of companies. We can't afford to build infrastructure and not product. Vercel gives us the foundation to move as fast as we need to."

— Fatima Rizwan, Founder & CEO @ Okara

Consolidating eight model providers behind one gateway

Okara's infrastructure demands scale quickly with its user base, so the team has worked to keep the plumbing invisible. Originally, the backend talked to eight model providers through separate SDKs, each carrying its own key management, image handling, and edge cases. Expanding to open-source models made that approach unworkable. Every new provider meant an engineer paused product work to write an adapter. Retry logic, fallback routing, and provider health monitoring all lived in Okara's codebase and required manual upkeep.

Moving to Vercel AI Gateway removed that burden. The gateway replaced every custom integration with a single configuration. Retry and fallback logic shifted out of Okara's code and into Vercel's routing layer, with zero-data retention support for the company's privacy-sensitive secure chat feature.

The operational effect is immediate: when a new model ships, Okara can expose it to users the same day through Gateway. No adapter development, no edge case testing, no deploy cycle. Full stack developer Boney Hernandez describes the difference plainly: "Before AI Gateway, every new model provider meant new keys, new dashboards, new billing. The overhead was constant and it had nothing to do with actually building."

Tightening the agent loop with sandboxes

Okara also runs agent workflows inside Vercel Sandboxes, which the team adopted the day they launched. Rizwan saw the announcement on X and building began immediately.

The practical use case: Okara's SEO agent scans a user's site for technical problems and then writes code to fix them. When it finds an issue, it spins up a Sandbox and runs the analysis in an isolated environment. The findings go to a coding agent, which opens a pull request with the fix, ready for a developer to review and merge. Detection, analysis, and code change happen automatically with a human making the final call before anything goes live.

Hernandez notes the team evaluated alternatives: "We evaluated other options, but the answer was always Vercel Sandbox. It spins up instantly and just works."

A deployment cadence that matches the product

With 120,000 websites on the platform, Okara ships to production six or seven times a day, and every improvement reaches customers the day it ships. New AI models follow the same pattern, arriving for users the same day they're released.

The company is expanding its agent suite and moving upmarket to serve larger teams, which means more users, more agents, and more tokens. For a four-person team carrying the growth load of 120,000 companies, keeping infrastructure out of the critical path isn't an optimization; it's a requirement.