Governed Data Integrations
Connect hundreds of data sources — databases, warehouses, SaaS, object storage, streaming and files — into the governed lakehouse and enterprise ontology, with residency, classification and access policy enforced by default.
Hundreds of Sources
Databases, data warehouses, SaaS applications, object storage, streaming feeds, and flat files — landed in the lakehouse with incremental ingestion.
Mapped to the Ontology
Every source is mapped into the enterprise ontology, so analytics, dashboards, and grounded AI reason over the same trusted, attributed data.
Governed by Default
Connections honour residency, classification, and access policy automatically — you unify data without copying it out of your control.
Insights integrations connect hundreds of data sources — databases, data warehouses, SaaS applications, object storage, streaming feeds and flat files — into the governed lakehouse with incremental ingestion. Every source is mapped into the enterprise ontology and honours residency, classification, and access policy by default.
Insights is only as good as the data it can reach. Rather than copying data out of your control or building a bespoke pipeline for every system, you connect each source once and land it in the lakehouse with governed, incremental ingestion. Because every source is mapped into the enterprise ontology, analytics, dashboards, and grounded AI all reason over the same trusted, attributed data.
Integrations in the Scrydon platform
One integrated, sovereign architecture. Here is where Integrations sits — highlighted against the full stack it works with.
The AI OS for Humans & AI Agents to enable your processes
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Link your processes, knowledge & data to ontologies.
Unified storage, structured compute, and secure multi-modal data processing.
Autonomous operatives with specialised skills executing tasks across systems.
Sovereign pipelines, federated APIs, and seamless connector meshes.
Secure domain federation, trusted data sharing, and cross-boundary intelligence.
Integrations in depth
Pipelines
Broken processes live in the gaps between systems. The Integrations layer of the AI OS closes those gaps, connecting securely and seamlessly to the operational tools you already rely on.
We provide a vast library of built-in integrations for immediate connectivity to standard CRMs, databases, and enterprise applications.
To ensure maximum flexibility, the platform natively supports open standards—including OpenAPI, MCP, and A2A. This standard-first architecture makes it incredibly easy to build and deploy custom integrations, allowing the full platform to interact with any proprietary system or specialized tool within your infrastructure.
Connect once, govern everywhere
Each source is connected once and ingested into the lakehouse incrementally, then mapped into the enterprise ontology so it joins the same semantic model as everything else. There are no bespoke pipelines per system, and nothing leaves your control: residency, classification, and access policy travel with the data by default.
Broad connectivity — Databases, warehouses, SaaS, object storage, streaming, and flat files — connected through governed, incremental ingestion.
Ontology-mapped — Every source is mapped into the enterprise ontology, so all analytics and AI reason over consistent, attributed data.
Policy by default — Residency, classification, and access policy are enforced on every connection automatically — governance is not an afterthought.
No data exfiltration — You unify the data without copying it out of your control, and without building bespoke pipelines for each system.
Trusted analytics start with trusted data
Self-service analytics and grounded AI are only as dependable as the data beneath them. By unifying hundreds of sources into one governed lakehouse and ontology — with residency, classification, and access policy enforced by default — Insights gives every dashboard, query, and AI answer the same trusted, attributed foundation, without bespoke pipelines or loss of control.
Frequently asked questions
What data sources can Insights connect to?+
Does ingesting data mean copying it out of my control?+
How does the ontology fit in?+
Do I need a custom pipeline for each system?+
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Prefer to write? Email hello [at] scrydon.com and we will get back to you.
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