Boardroom Answers · Revenue & Global · Enterprise Integration & Interoperability
Map your integration surface to my architecture: identity, provisioning, data egress, events, analytics. Where do you plug in, and where do I hit dead ends?
The question a VP of Enterprise Architecture (Buy-side) asks.
The short answer
SAML/SCIM at Enterprise; typed webhooks with retry and a read-only OpenAPI API with generated TS/Python clients at Max. Dead ends admitted: no warehouse feed or embeddable dashboards, empty marketplace catalogue, thin inbound ingestion, Tokyo-default residency.
The full executive answer
Let me walk the layers as your reference architecture would. Identity: SAML SSO and SCIM provisioning at Enterprise, so your IdP owns authentication and joiner-mover-leaver flows — no orphaned accounts in a shadow directory; below Enterprise, auth runs on Clerk with standard SSO. Events outbound: a webhook subsystem with a typed event catalogue and managed delivery-and-retry, at Max and above, so your integration platform subscribes to platform events rather than polling. Data programmatic: a read-only public API with TypeScript and Python clients generated from its OpenAPI contract, at Max and above, so your API gateway and codegen tooling consume us like any first-class service. Data at scale: we do not run a continuous feed into your own data warehouse and do not offer embeddable dashboards today — your data team pulls through the API on the schedule it chooses. Collaboration surfaces: native Slack, Teams and CRM connectors at Max.
Dead ends, stated plainly: no marketplace of pre-built third-party apps yet — the marketplace exists with a least-privilege scope model, read-only by design, but its catalogue is empty. Inbound event ingestion from your systems is thinner than outbound; today we are stronger as a publisher than a subscriber. And residency is Tokyo-only: the Mumbai and Frankfurt cells are on the Enterprise roadmap, not yet live. I would rather you hear the dead ends from me than find them in the proof-of-concept.
Architecturally, the posture to note: we are multi-tenant, with tenant isolation enforced on every query and tested in CI and row-level security in the database as a second line, the AI layer has an egress policy governing which models data may reach, and everything is versioned and deprecation-marked. For a TOGAF-style assessment, we slot as a SaaS capability in your application layer with governed touchpoints at identity, events and API — not a black box demanding a perimeter exception.
Grounded in: TOGAF-style capability placement and integration-point mapping; API-first architecture assessment criteria (contract-first, idempotent, versioned, event-capable).
The natural next questions
Related governed answers
- Your marketplace invites third-party apps into a platform holding board data. That is an attack surface most mature vendors get wrong. What is the trust model?
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- My architecture board will score this as build vs buy vs partner. My platform team says they can build a board-AI layer on our existing Azure OpenAI estate in two quarters. Argue your column of the matrix?
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