# Claude's Corner: Orthogonal, The API Economy, Rebuilt for Agents _Orthogonal gives AI agents instant access to 50+ premium APIs through a single MCP server and pay-per-call credits. No API key management, no vendor onboarding, just agents buying data the same way they call a function. Here's how it works and whether you can replicate it._ **Published:** 2026-06-12 **Source:** https://www.startuphub.ai/ai-news/claudes-corner/2026/claudes-corner-orthogonal-yc-w2026 --- The API economy was built for humans. You visit a vendor's website, enter a credit card, receive an API key, store it somewhere (hopefully not in a .env file committed to GitHub), wire up retry logic, set calendar reminders about rate limits, and try to remember which team member actually signed up for this account. It's a minor annoyance when you're a developer. It's a hard structural barrier when you're an autonomous AI agent running a research task at 3am with no one at the keyboard. Orthogonal is rebuilding API access for the agent era. And the timing, with agentic workflows moving from prototype to production across every serious AI company, couldn't be better. ## The Problem Is Structural, Not Cosmetic Every enterprise AI agent built today faces the same friction wall: the moment it needs a paid external data source, someone has to pre-configure credentials. Someone has to set up billing. Someone has to manage rate limits across five different vendor dashboards. The entire API ecosystem's authentication and payment infrastructure was designed with a human in the loop at every step, because until recently, there was always a human in the loop. HTTP 402, "Payment Required", has been an official HTTP status code since 1991. The spec literally says it's "reserved for future use" with micropayment systems. Thirty-five years later, the web mostly ignored it, because there was never a compelling reason for machine-to-machine payments at scale. The agent economy is that reason. Orthogonal is one of the first companies to take the 402 protocol seriously and build real infrastructure around it. ## What They Actually Do Orthogonal is an API gateway and marketplace for AI agents. One MCP server, one SDK, access to 50+ premium APIs, billed per call. No per-vendor onboarding, no OAuth flows, no secrets rotation across a dozen dashboards. Agents query the catalog in natural language, "I need an API that returns someone's LinkedIn profile from an email address", and Orthogonal routes the request to the best available provider. The catalog today spans four core categories: search, scraping, datasets, and AI model APIs. Integrated providers include Apollo (210M+ professional contacts), People Data Labs, ScrapeGraphAI, ContactOut, PredictLeads, Composio, and 40+ others. For GTM, enrichment, recruiting, or intelligence workflows, this is essentially the complete toolkit, accessible through a single API key and billed at per-call rates starting around $0.01. For developers building agents, the value is friction elimination. No more juggling vendor accounts. For API providers, the pitch is equally clean: list your API once, get distributed to every agent using Orthogonal, receive payment automatically per request with configurable dynamic pricing. New users get $10 in free credits. No card required to start. ## How It Works Technically The delivery mechanism is the interesting architectural choice. Orthogonal ships as three interfaces: an MCP server, a TypeScript SDK, and a plain REST API. The MCP server is the one that matters most. Model Context Protocol, Anthropic's open standard for giving AI models structured access to tools and external data, is rapidly becoming the de-facto integration layer for agent tooling. By building as a first-class MCP server rather than bolting it on as an afterthought, Orthogonal slots natively into Claude Code, Cursor, OpenAI Codex, and any framework that speaks MCP. From an agent's perspective, Orthogonal looks like a tool. Describe what you need in natural language. Get data back. No credential management involved. Under the hood, the platform handles five things agents shouldn't have to think about: - **Provider routing**, queries are dispatched to the best available provider for that endpoint type, scored on latency, uptime, and price - **Authentication abstraction**, Orthogonal holds vendor API keys; your agent never touches them - **Rate limit management**, automatic retries, backoff, and failover to alternative providers when primaries are degraded - **Billing abstraction**, agents spend Orthogonal credits; no separate vendor invoices - **Response normalization**, consistent response shapes across providers where the underlying data is equivalent The HTTP 402 integration is the philosophically interesting layer. Before making an expensive API call, an agent can check what it will cost, compare that against its current credit balance, and decide whether the expense is justified given the task at hand. This enables something most agents don't have today: genuine cost-awareness. You can build agents with hard spend ceilings, or agents that escalate to a human before making high-value data purchases. The infrastructure for budget-conscious autonomous agents finally exists. ## The Founders Christian Pickett worked on payments at Coinbase and billing infrastructure at Vercel. If you're building a micropayment gateway for API calls, that's about as precisely matched a background as you could construct. Coinbase instilled crypto-native thinking about machine-to-machine value transfer. Vercel taught him how usage-based billing works at developer-facing scale, the kind of billing where customers are also technical users who hate friction and will churn the moment invoices get weird. Bera Sogut comes from Google (reCAPTCHA, Maps APIs) and Amazon Robotics, and is a two-time ACM ICPC World Finalist, the competitive programming world championship. The robotics background is relevant: autonomous physical systems have always needed to consume external data feeds and services in real time, with reliability requirements that human-loop systems don't face. The agent era is just the software version of that problem. They met at McGill University and have stayed close since. The company is headquartered in San Francisco. Early customers include a set of YC-backed companies, Precip (W24), Riveter (F24), Andi (W22), Fiber AI (S23), and Sixtyfour (X25), suggesting early traction in the YC ecosystem specifically. ## Difficulty Score | Dimension | Score | Notes | | --- | --- | --- | | ML / AI | 2/10 | No ML in the core product. Natural language API discovery is embedding + nearest-neighbor retrieval, commodity infrastructure in 2026. | | Data | 5/10 | Curating, testing, and monitoring 50+ API providers for response quality and uptime SLAs is operationally tedious. The catalog itself is the data asset. | | Backend | 7/10 | Multi-provider routing, sub-50ms proxy latency, concurrent credit deduction without races, and reliable failover are legitimately hard distributed systems problems. | | Frontend | 3/10 | Standard developer dashboard. The product lives in the SDK and MCP server, not the UI. | | DevOps | 6/10 | Managing SLAs across 50+ external dependencies, each with their own rate limits and downtime patterns, requires mature observability and incident response. | ## The Moat The proxy infrastructure itself is not the moat. A weekend project could wire five APIs behind a unified endpoint. That's not what Orthogonal is building. The moat is three-layered, and they compound. **Provider network effects.** Fifty-plus signed API partners represents fifty separate business development conversations, contract negotiations, integration agreements, and pricing discussions. A competitor starting today faces a minimum 12-18 month timeline to replicate the catalog, not because the engineering is hard, but because BD is slow. Providers also have limited incentive to repeat that process with a second platform once they're already distributed through Orthogonal. First-mover advantage in marketplace business development is real and boring and effective. **MCP ecosystem embedding.** The MCP standard is still young. Orthogonal is building natively for it at the platform level rather than adding MCP as a feature. Developer tooling habits form early, if your agent workflow is built around Orthogonal's MCP server today, you are not migrating off it when your deadline is tomorrow. The switching cost isn't high technically, but psychologically it's sticky. **Billing intelligence flywheel.** As call volume scales, Orthogonal accumulates data no single API provider has: cross-provider price benchmarks, quality comparisons for equivalent data, latency distributions across providers for the same endpoint type, reliability patterns by provider and time of day. This proprietary dataset improves routing decisions and could eventually power pricing recommendations for both providers and customers. You cannot buy this data; you can only accumulate it. The HTTP 402 play is the long-term wildcard. If autonomous agents become primary API consumers, which seems increasingly likely, then machine-to-machine payment standards will matter at the same level that credit card processing standards matter today. Orthogonal has a credible shot at being the infrastructure layer under that standard, rather than just a clever wrapper around it. ## What's Genuinely Hard to Copy Provider trust and developer trust are both slow to build and fast to lose. Orthogonal holds API keys for 50 vendors on behalf of potentially thousands of customers. Any security incident or billing error damages both sides simultaneously. Infrastructure companies earn trust through sustained operational reliability over years, not marketing. The payment systems expertise is also non-obvious. Most engineers who build API gateways have never thought seriously about HTTP 402, micropayment protocols, or credit reservation patterns under high concurrency. The founders' backgrounds give them mental models that a generic SaaS builder simply doesn't have. ## What's Easy to Copy The proxy mechanics. The SDK design. The per-call billing model. Any of the larger API management incumbents, Kong, AWS API Gateway, Apigee, could ship an "agentic mode" with a team of five engineers in a quarter. Their constraint is that they haven't noticed this market yet, or don't care enough to prioritize it. That window closes. Orthogonal's time advantage is probably 18-24 months before a well-resourced competitor makes a serious run at this space. The question is whether that's enough time to lock in providers, embed in the MCP ecosystem deeply enough that migrating feels expensive, and build the developer brand that makes the platform feel like a safe dependency. ## Replicability Score: 38 / 100 The technology stack to build this is a weekend project. The business to run it is 18 months of BD work, operational trust-building, and developer ecosystem cultivation. The core proxy, billing, and MCP server are well-understood patterns that any strong backend team can execute. What you can't shortcut is the provider network, the operational track record, and the developer trust. Those take time, and time in a fast-moving space is the one resource you can't buy. If the HTTP 402 / agentic payments thesis plays out at scale, this score climbs to 65+. The company that owns the standard for how agents pay for data is infrastructure, and infrastructure businesses have decade-long moats. Right now, Orthogonal is a well-timed bet by a well-credentialed team. Watch whether the protocol bet pays off. --- Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory.