SursaTech (Sursa Technology Private Limited) is an AI-native product engineering and consulting company founded in 2017 in Kathmandu, Nepal, building production AI agents, RAG and knowledge systems, AI-enabled SaaS products, automation and integrations, and QA leadership for clients in Nepal, Japan, Norway, the United States and the United Kingdom, and operating its own products (Humafu, AcademyKit, Buy Me a Momo). Its public machine surface is an A2A 1.0 agent — the SursaTech AI Advisor — served as a conformant agent card at /.well-known/agent-card.json with a JSON-RPC endpoint at api.sursatech.com/api/a2a: ten skills covering company knowledge (profile, services, portfolio, process, pricing), lead-requirement capture, tentative project estimates and guarded consultation booking, payment and cancel/reschedule flows. Any agent can self-register anonymously for an opaque bearer token; the provider publishes RFC 8414/OIDC authorization-server metadata, RFC 9728 protected-resource metadata, an RFC 9727 api-catalog, an agentskills.io skill index and an llms.txt, but no OpenAPI, SDK, MCP server, status page, pricing for the API, or legal pages.
SursaTech is listed with 1 API on the APIs.io network. Tagged areas include AI Agents, A2A, AI Consulting, Product Engineering, and Software Development.
SursaTech’s developer surface includes pricing, documentation, authentication, and 24 more developer resources.
Regulatory Posture applies to this provider. Its tags matched the
Horizontal (data, software, accessibility, platform) regime, so
Regulatory Posture carries 15 points of the composite.
If this regime is wrong for your business, say so on your
provider repo — the
applicability map is public and we will correct it.
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for
this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero:
never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and
several others — scorable at all.
The six quality facets above are damped to 85 points between them,
because the conditional facet above carries the other
15. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 85% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
An A2A 1.0 agent (JSON-RPC 2.0 over HTTP POST, streaming declared) exposing ten skills: get_company_profile, get_services, get_portfolio_projects, get_development_process, estim...
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