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 17.0/100 (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.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
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