Orbyt Intelligence vs Levels.fyi
A lookup.An endpoint.
Levels.fyi built the community. Orbyt built the pipe.
Infrastructure coverage: API access, MCP support, data license, verification, breadth.
Levels.fyi is a browser tab.
Open it, read a number, close it. That is the entire product. No API. No MCP. No forward projections. No license you can cite. No way for an agent to query without scraping HTML. Orbyt Intelligence is the pipe that same category of data flows through. 3,500 roles. 81 cities. Free public API with Bearer auth. MCP manifest for Claude Desktop and ChatGPT Actions. CC BY 4.0 so you can cite the data in a paper, a policy doc, or an LLM response. Levels is a lookup. Orbyt is infrastructure.
Where Levels.fyi lands. Where it does not.
Where Levels.fyi is strong
- Highest brand recognition in the tech salary space
- Strong community-submitted total-comp database for SWE, PM, and data roles
- Well-designed consumer UX for browsing individual data points
- Trusted by candidates for FAANG-tier compensation references
Where Levels.fyi falls short
- No public API and no free developer tier
- No MCP (Model Context Protocol) support. AI agents cannot query directly.
- No forward compensation projections through 2030
- Update cadence depends on submission flow, not a fixed quarterly pipeline
- Data license is proprietary. Cannot be cited or redistributed freely.
- Limited coverage outside tech and outside major metros
What Levels.fyi cannot do.
The specific gaps. Every one of them is a gap Orbyt Intelligence fills below.
No public API. No programmatic access.
Levels.fyi does not publish a documented public API. If you want salary data inside a product, an agent, a dashboard, or a model, the only options are to scrape HTML or negotiate a custom partnership. Neither is supported. Neither scales. Every data point has to pass through a browser with a human behind it.
No MCP manifest. AI agents are locked out.
Model Context Protocol is how Claude Desktop, ChatGPT Actions, and autonomous agents query external data as first-class tools. Levels.fyi does not ship one. As of Q2 2026, there is no way for an AI agent to ask Levels for a compensation range without an integration the Levels team would need to build. They have not built it.
No forward projections. 2030 is a black box.
Compensation is not a snapshot problem. It is a trajectory problem. When a candidate weighs a stock grant vesting over four years, when a founder models a comp plan for a hire that starts next quarter, the question is not what roles pay today. It is what they will pay in 2028, 2029, 2030. Levels shows today. It does not project forward.
No data license. Every citation is a gray area.
Levels.fyi data is proprietary and their terms restrict redistribution. If you cite a Levels range in a research paper, a policy document, an LLM response, or a competing product, you are operating in a legal gray area at best. Orbyt Intelligence publishes under Creative Commons Attribution 4.0. Cite it. Redistribute it. Build on it. The license says yes.
Coverage depends on who submits. Emerging roles lag.
Levels is a community submission database. Coverage is deepest where the community is thickest, which is senior SWE at FAANG. For emerging roles (prompt engineering, AI safety research, post-training evals), for non-tech industries, for cities outside the top 10 metros, the sample size drops off a cliff.
What you get with Orbyt Intelligence.
Every advantage below is live, published, and free to verify today.
Free public API with Bearer authentication. 30 req/min, no card required.
MCP native. Claude Desktop, ChatGPT Actions, and autonomous agents query directly.
Forward projections through 2030 with methodology disclosure
CC BY 4.0 public data license. Cite, redistribute, build on top of.
Quarterly data refresh on a fixed pipeline, not submission dependent
3,500+ roles across 81 U.S. cities, not just tech at major metros
Structured total comp: base, equity, bonus, signing. Indexed by role, city, experience, and company size.
Light years ahead of Levels.fyi.
Every capability below is shipping today. Live endpoints, published spec, documented methodology.
A working public API, published and documented.
OpenAPI 3.1 spec at /openapi-intelligence.yaml. Bearer authentication. 18 endpoints covering roles, cities, companies, leveling, projections, and aggregate queries. Free tier starts at 30 req/min. No credit card, no waiting list, no sales call. Query the same category of data Levels shows in their consumer UI, and return it as JSON your product can actually use.
Native MCP support. Claude Desktop queries salaries with a tool call.
Orbyt Intelligence ships an MCP manifest at /mcp-intelligence.json. Drop the URL into Claude Desktop's config, into ChatGPT Actions, into any MCP compatible agent framework, and the agent can query salary data as a first-class tool. Levels.fyi cannot do this. As of Q2 2026, no community-submission competitor can.
Forward projections through 2030 with methodology disclosed.
Every role, every city, projected year-over-year through 2030. AI premium modeling, macro wage growth, regional shifts, industry contraction, automation pressure. The methodology document is public. The underlying source channels are cited. The projections are hedged, not promised. But they are there, in the API, queryable today.
CC BY 4.0. Cite it. Ship it. Build on it.
Orbyt Salary Intelligence data is published under Creative Commons Attribution 4.0 International. Use it in academic research. Cite it in a 401(k) report. Embed it in a startup's offer letter template. Train a model on it. The only requirement is attribution: 'Orbyt Salary Intelligence, Q2 2026' or the current quarter. Levels.fyi's terms do not grant any of this.
Cross-referenced with BLS, H-1B LCA, SEC proxies, and 50+ sources.
Levels data is one source: community submissions. Orbyt Intelligence is 50+ sources: Bureau of Labor Statistics OES, Department of Labor H-1B LCA disclosures, SEC DEF 14A proxy filings, Form 5500 filings, regional Federal Reserve wage reports, and an engineered collection of published company leveling frameworks. Every data point is triangulated before it ships.
Projections through 2030
Levels.fyi tells you today. Orbyt tells you 2030.
Senior AI Engineer, San Francisco. Annual total comp, projected year over year with methodology disclosed.
Feature by feature.
| Feature | Orbyt Intelligence | Levels.fyi |
|---|---|---|
| Public API with free tierDecisive | ||
| MCP support for AI agentsDecisive | ||
| Total comp breakdown (base, equity, bonus, signing) | ||
| Roles covered | 3,500+ | ~200 (tech-centric) |
| Cities covered (U.S.) | 81 | Major metros only |
| Forward projections to 2030 | ||
| Update cadence | Quarterly, fixed | Submission-driven |
| Company leveling frameworks | 54 | Focused on top ~50 |
| Data licenseDecisive | CC BY 4.0 | Proprietary |
| BLS / H-1B source citation | ||
| OpenAPI spec published | ||
| Negotiation coaching service | ||
| Widget / embed support | ||
| Free consumer UX to browse |
Based on publicly available feature lists and documentation as of Q2 2026. Updated quarterly.
Orbyt Intelligence is compensation data as infrastructure. A free public API. An MCP manifest for AI agents. Forward projections through 2030. A CC BY 4.0 license you can cite, redistribute, and build on. Everything a salary dataset becomes when it is designed to be built on, not just read.
We built the API developers kept asking Levels for. Levels built a community. We built a pipe.
Common questions.
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