Pascal AI
Pascal AI (Pascal AI Labs) is an institutional-finance AI company building context-driven, MCP-native research agents that turn enterprise and market data into investment insights for hedge funds, asset managers, investment banks, and private-markets firms. Pascal sits inside Excel, PowerPoint, Word, email, and the browser through an Agent Control Center, ships 25+ pre-built research agents, maintains a persistent knowledge graph and memory across every document a team has touched, and returns fully cited outputs with RBAC enforcement. It deploys inside the customer VPC or on-premises and exposes an enterprise API & SDK (Python, TypeScript, REST) plus finance-ready MCP connectors. Founded in 2024 in Bangalore, Pascal AI raised a $3.1M seed round in 2025 led by Kalaari Capital with Norwest Venture Partners, Antler, and Info Edge Ventures. It publishes SOC 2 Type II, ISO 27001, and GDPR compliance. No public API specification or developer portal is published; developer surfaces are gated to enterprise customers.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles Pascal AI the way a machine reads it — 1 machine-readable artifact, 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 — Pascal AI scores 18.2/100 (emerging), with a separate agent-readiness read of 0/100 (human only). 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. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-09-08 · rubric v0.20.0
Put this on your own site. The badge is drawn live from Pascal AI's current Kin Score — paste it once and it updates itself every time the score is recomputed. It follows your visitor's light or dark setting, and it links back here so anyone who sees it can read the full breakdown.
<!-- Kin Score · API Evangelist -->
<a href="https://providers.apievangelist.com/providers/pascalailabs/"
title="Pascal AI on API Evangelist — API profile and Kin Score">
<img src="https://apis.io/badge/pascalailabs.svg"
alt="Pascal AI Kin Score — API readiness rating by API Evangelist" width="150" height="150" loading="lazy">
</a>[](https://providers.apievangelist.com/providers/pascalailabs/)<!-- Kin Score · API Evangelist -->
<a href="https://providers.apievangelist.com/providers/pascalailabs/"
title="Pascal AI on API Evangelist — API profile and Kin Score">
<img src="https://apis.io/badge/pascalailabs/card.svg"
alt="Pascal AI Kin Score — API readiness rating by API Evangelist" width="340" height="120" loading="lazy">
</a>More shapes, themes and sizes → · Score as JSON · How badges work
How we profile Pascal AI
Each block below is one kind of artifact we hold for Pascal AI. 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.
Security Posture 1
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 Pascal AI — 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 1
Portal, sign-up, and the first successful call
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 1
Pagination, idempotency, versioning, errors, and events
Access & Security 3
Authentication, authorization, and security posture
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/pascalailabs · machine-readable index on apis.io
This is an independent, third-party profile of Pascal AI, 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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you will get a person, not a form — we will tell you exactly which public URLs this profile was built from.