Riverlane
Riverlane is a Cambridge (UK) quantum computing company building the quantum error correction (QEC) stack. Its two product lines are Deltaflow — a real-time QEC system covering qubit data readout, decoding, logical operations and orchestration, running error correction on up to 250 physical qubits with the proprietary Local Clustering Decoder — and Deltakit, an Apache-2.0 open-source Python SDK for designing, generating, simulating, decoding and analysing QEC experiments. The public developer surface is the Deltakit cloud service at https://deltakit.riverlane.com/proxy, a bearer-token API with two coexisting versions: a GraphQL endpoint (/api/graphql, API v1) and an asynchronous task REST API (/api/v2/tasks/add|get|kill, API v2). Both front Riverlane's proprietary decoders (Ambiguity Clustering, Local Clustering, Collision Clustering), leakage-aware decoding and simulation, iSWAP native-gate circuit generation, and stability-experiment generation. Riverlane publishes no OpenAPI or AsyncAPI document; the machine-readable contract is the open-source client library at github.com/Deltakit/deltakit, which is where every endpoint recorded in this profile was read from.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles Riverlane the way a machine reads it — 4 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Riverlane scores 28.6/100 (thin), with a separate agent-readiness read of 13/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-08-17 · rubric v0.11.0
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title="Riverlane on API Evangelist — API profile and Kin Score">
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How we profile Riverlane
Each block below is one kind of artifact we hold for Riverlane. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 1
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Deltakit Cloud API
Bearer-token cloud service backing the Deltakit SDK. Exposes the compute-heavy and proprietary parts of the QEC workflow that do not run locally: leakage noise generation and si...
Security Posture 3
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Riverlane — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 6
Pagination, idempotency, versioning, errors, and events
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/riverlane · machine-readable index on apis.io
This is an independent, third-party profile of Riverlane, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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