Microsoft 365 Copilot can now tap enterprise file shares without forcing a wholesale migration to the cloud: NetApp’s new connector brings on‑prem and cloud NetApp data into Copilot while preserving item‑level security, offering containerized deployment options, and promising high performance for document ingestion and indexing.
Enterprises that have invested in NetApp storage — from on‑prem ONTAP arrays to Azure NetApp Files — have long faced a tradeoff: either migrate critical datasets into Microsoft 365 to get Copilot to “see” them, or accept that Copilot’s answers will lack the context of corporate files. NetApp’s Connector for Microsoft 365 Copilot moves to eliminate that tradeoff by acting as a bridge between NetApp data stores and Microsoft’s Graph indexing pipeline. The connector is presented by NetApp as a purpose‑built integration that can extract file content and permissions, hand those artifacts to Microsoft’s indexing stack, and thereby let Copilot ground responses in enterprise data while keeping governance intact.
This announcement arrives against a broader industry trend: Microsoft’s Copilot ecosystem increasingly relies on Graph Connectors and custom connectors to make third‑party and on‑premises data first‑class for Copilot and Business Chat. That architectural path — converting files into searchable, indexed representations and exposing them to Copilot with permission checks — is documented in Microsoft’s developer and product communications and has been rolled out in stages across previews.
That said, a specific claim that the NetApp connector “operates at 40 times the speed of the previous generation” cannot be corroborated from NetApp’s public documentation or the Microsoft blog posts at the time of reporting. NetApp performance blogs discuss multi‑fold improvements in underlying AFF/ONTAP hardware and GDS IO performance (2x+ in some storage benchmarks), but an explicit 40× figure for the connector’s end‑to‑end ingestion speed does not appear in official release notes or community documentation that are publicly available. Treat any “40×” figure as an unverified performance claim unless NetApp or a third‑party benchmark provides reproducible test details (workload, dataset, connector version, network topology, and metrics).
When engaging with NetApp or a systems integrator, ask for:
However, IT leaders should be pragmatic: verify deployment models (VM/GCA vs. container), validate performance claims against your own datasets and topology, and ensure governance questions — where embeddings are stored, how long OCR artifacts persist, and how permissions map into Entra/Microsoft Graph — are explicitly answered before a production roll‑out. NetApp’s public documentation and Microsoft’s architecture guidance provide the technical starting point, but enterprise risk and compliance teams will need to treat the connector as they would any system that expands the reach of AI into sensitive data estates.
Source: Windows Report NetApp Neo Connector Supercharges Microsoft 365 Copilot with External Data
Enterprises that have invested in NetApp storage — from on‑prem ONTAP arrays to Azure NetApp Files — have long faced a tradeoff: either migrate critical datasets into Microsoft 365 to get Copilot to “see” them, or accept that Copilot’s answers will lack the context of corporate files. NetApp’s Connector for Microsoft 365 Copilot moves to eliminate that tradeoff by acting as a bridge between NetApp data stores and Microsoft’s Graph indexing pipeline. The connector is presented by NetApp as a purpose‑built integration that can extract file content and permissions, hand those artifacts to Microsoft’s indexing stack, and thereby let Copilot ground responses in enterprise data while keeping governance intact. This announcement arrives against a broader industry trend: Microsoft’s Copilot ecosystem increasingly relies on Graph Connectors and custom connectors to make third‑party and on‑premises data first‑class for Copilot and Business Chat. That architectural path — converting files into searchable, indexed representations and exposing them to Copilot with permission checks — is documented in Microsoft’s developer and product communications and has been rolled out in stages across previews.
What the NetApp Connector actually does
Core functions, at a glance
- Connects NetApp file sources to Microsoft 365 Copilot — including Azure NetApp Files and ONTAP‑based file shares — so Copilot can answer prompts informed by business documents without migrating the raw files into OneDrive or SharePoint.
- Extracts item‑level ACLs and maps them into Microsoft Graph so permissions stay enforced: users only see results they’re authorized to view. NetApp explicitly calls this out as a v1.1 improvement.
- Supports broad file formats and media types — Office documents, PDFs, HTML, CSV/JSON/XML, ZIP (with iteration over contents), and on request additional audio/image OCR/transcription features.
- Handles large files via chunking and parallelization: the connector splits and pipelines large documents so they can be ingested into Microsoft Graph despite API size constraints. A community README and implementation notes document chunking and parallel extraction as central design features.
Deployment and topology notes
NetApp and community documentation describe a few deployment flavors that reflect different release stages and customer needs:- A Graph Connector Agent (GCA) VM model where NetApp’s connector interfaces with Microsoft’s Graph Connector Agent — documented in Microsoft’s Azure Architecture blog as a supported route for Azure NetApp Files and on‑prem shares. This model is consistent with Microsoft’s Graph Connector architecture and has been the primary path for some customers.
- A containerized variant surfaced in NetApp’s Github README and community artifacts that describes a containerized connector with RESTful APIs, parallelized extraction, and rapid deployment. This form is pitched as faster and simpler to operate in modern Kubernetes or container hosting contexts.
What’s new (and what’s true): features enterprises should care about
Item‑level permissions preserved
NetApp’s v1.1 notes emphasize item‑level ACL extraction and automated transfer of those principals into Microsoft Graph, which means results surfaced to Copilot can be permission‑aware. For enterprise security and compliance teams this is the single most important claim: the connector is designed to not collapse access controls into a single “connector user” view, but to maintain per‑file authorization semantics as they map into the Microsoft 365 identity plane. This is consistent with the Graph Connector model and addresses one of the chief objections to third‑party connectors in regulated environments.Broad format and content support, with OCR and transcription on the roadmap
NetApp documents and community messaging list robust format support: Office files, PDFs, HTML, structured text, and container handling for ZIPs with iterative extraction. Image OCR and audio transcription are listed as available on request, and NetApp’s broader partnership with GPU vendors signals an emphasis on accelerated processing for heavier workloads (see the NVIDIA collaboration below). Enterprises should treat OCR/transcription as supported but potentially requiring additional configuration, resources, or feature flags.Large‑file ingestion and chunking
Microsoft Graph and many indexing APIs have message size limits; NetApp’s connector implements document chunking and parallel pipelines so very large files can be broken down and uploaded as indexed content. That design choice is crucial for organizations that maintain large technical manuals, datasets, or archives that would otherwise exceed Graph ingestion limits. Implementation notes in community repositories confirm that chunking and parallel extraction are part of the connector’s feature set.Containerized, faster deployment — but check the docs
NetApp presents a containerized variant that supports modern deployment options and API interaction. The NetApp README mentions typical container deployment times measured in minutes and lists an API interface for management. Community documentation runs alongside Microsoft guidance referencing the GCA VM path, indicating that both models are in circulation. This means IT teams can pursue a Kubernetes/Helm or container approach where supported, but should verify the exact installation artifacts, supported orchestrators, and compatibility matrix for their version.Performance, GPUs, and the “40x” claim: what can be verified
NetApp and partners have been explicit about accelerating AI pipelines with GPU‑enabled stacks. NetApp’s publicized collaboration with NVIDIA targets agentic AI and inference acceleration, and NetApp’s ONTAP systems have documented throughput improvements for AI workloads when paired with NVIDIA GPUDirect and optimized storage stacks. These investments create a plausible foundation for better OCR, faster content extraction, and high‑throughput ingestion.That said, a specific claim that the NetApp connector “operates at 40 times the speed of the previous generation” cannot be corroborated from NetApp’s public documentation or the Microsoft blog posts at the time of reporting. NetApp performance blogs discuss multi‑fold improvements in underlying AFF/ONTAP hardware and GDS IO performance (2x+ in some storage benchmarks), but an explicit 40× figure for the connector’s end‑to‑end ingestion speed does not appear in official release notes or community documentation that are publicly available. Treat any “40×” figure as an unverified performance claim unless NetApp or a third‑party benchmark provides reproducible test details (workload, dataset, connector version, network topology, and metrics).
Security, governance, and compliance — practical realities
Permission mapping and enforcement
The connector’s ability to extract item‑level ACLs and map them into Microsoft Graph is its strongest governance argument: it allows Microsoft 365’s native controls (Entra IDs, role assignments, DLP, and Purview policies) to sit over the indexed content rather than forcing a parallel security model. That reduces the need for bespoke entitlement mappings and preserves auditability inside Microsoft’s telemetry and compliance tooling. NetApp documents this behavior as a design goal for v1.1.Where indexing artifacts live
Semantic indexing and vector embeddings — the kind of representations Copilot uses to ground queries — must be managed carefully. Enterprises should ask precisely where vectorized representations, OCR outputs, and extracted metadata are stored, whether they are encrypted at rest, and what retention and purge policies apply. Microsoft’s Copilot and Graph Connector guidance emphasizes permissions and explicit upload behaviors, but organizations should run data‑handling, retention, and auditability checks before onboarding sensitive repositories. Microsoft’s own Copilot guidance recommends staged testing and explicit permission controls for these scenarios.Operational exposure and threat modeling
A connector that mounts SMB shares or accesses cloud volumes necessarily increases the attack surface of the indexing pipeline. Best practice operational controls include:- Limit connector network access to the minimal set of IPs and endpoints required for Graph ingestion.
- Run the connector in a hardened, monitored environment (Azure private endpoints, dedicated service accounts, conditional access policies).
- Validate item‑level permission mapping on a representative dataset before broad sync.
- Monitor and audit both the connector and the Microsoft Graph ingestion timeline to detect anomalies.
Deployment checklist: how IT teams should evaluate NetApp’s connector
- Inventory: identify the NetApp platforms (Azure NetApp Files, ONTAP clusters, Cloud Volumes ONTAP, FSxN, etc.) that will be in scope.
- Permissions audit: confirm that item‑level ACLs and identity mappings are consistent and that service accounts used by the connector have the minimum required privileges.
- Decide topology: choose between GCA (VM + Graph Connector Agent) and containerized deployment. Confirm supported orchestrators (Kubernetes, plain Docker, Azure Container Instances) and ensure compatibility with your network and security posture. NetApp community materials document both approaches; verify current packaging/version.
- Performance plan: prioritize which shares to index first, and run a pilot to capture ingestion throughput, CPU/GPU usage (if OCR/transcription is enabled), and network egress/ingress patterns. Avoid assuming vendor‑quoted performance numbers without a matching test scenario in your environment.
- Compliance and retention: define how long extracted metadata, OCR output, and embeddings are retained and where they live. Configure Purview, DLP, and audit logging accordingly.
- Operationalize: integrate connector alerts into SIEM, and plan for operational tasks (certificate rotation, credential lifecycle, connector upgrades).
Strengths and enterprise benefits
- No forced migration: keeps original files where they belong — in NetApp storage — while making their contents accessible to Copilot’s grounding pipeline. This reduces data movement, storage duplication, and the governance friction of mass migrations.
- Permission‑aware results: item‑level ACL extraction reduces example leakage and ensures Copilot’s surfaced answers respect existing access controls. That’s a major plus for regulated sectors.
- Flexible deployment: containerized packaging supports modern deployment patterns and faster provisioning; VM/GCA options exist for environments that require them.
- Practical ingestion features: chunking, multi‑threaded extraction, and parallel pipelines handle real‑world enterprise file sizes and archive formats.
Risks, limitations, and open questions
- Unverified headline performance claims: any bold “40×” speed improvement should be validated with reproducible benchmarks; NetApp’s public performance materials discuss multi‑fold storage throughput improvements in specific hardware configurations, not a universal 40× connector speedup. Enterprises should demand workload‑specific benchmarks.
- Mixed deployment messaging: documentation across NetApp community posts and Microsoft blogs reflects both VM/GCA and containerized approaches; ensure you’re following the correct installation path for your target version. Packaging differences can change prerequisites and firewall/network design.
- Index scope surprises: expanding the set of indexed locations (for convenience) can increase exposure; administrators must treat index scope and Copilot permissions as first‑class policy decisions. Microsoft’s Copilot preview materials and Graph Connector guidance emphasize explicit permission models, but the operational detail remains important.
- Dependency on Microsoft Graph quotas and semantics: ingestion behavior is subject to Graph API limits and changes; chunking mitigates content‑size limits, but teams should monitor quota usage and throttling.
Broader context: NetApp, NVIDIA, and the AI data pipeline
NetApp’s broader partnership with NVIDIA and its messaging about GPU‑accelerated inference and data pipelines indicates a strategic push to optimize storage and data services for agentic and reasoning AI workloads. Those investments aim to reduce latency and improve throughput for AI inference and large‑scale retrieval, which is relevant to OCR and indexing workloads that the connector may use. That said, storage/GPU co‑design accelerates the infrastructure side of AI workflows — organizations still must measure end‑to‑end latency and throughput for their specific content and query patterns.How to get started and what to ask your vendor
NetApp’s community pages and Microsoft’s Azure Architecture blog provide steps for requesting access, installation prerequisites, and demonstration assets. NetApp lists a “request access” flow for demos and POC sign‑ups; Microsoft’s architecture guidance lays out how to install and register the connector with the Graph Connector Agent where relevant. Enterprises should request an up‑to‑date deployment guide, a compatibility matrix (ONTAP versions, Azure NetApp Files SKUs, Kubernetes/Helm charts if available), and documented performance test artifacts.When engaging with NetApp or a systems integrator, ask for:
- A sample manifest of extracted attributes and permissions for a representative dataset.
- Proof of end‑to‑end encryption and retention controls for extracted OCR/text/embeddings.
- A reproducible performance test report using a dataset representative of your largest files (document count, average and max file size, typical file mix).
- Clear upgrade and rollback procedures for connector and Graph ingestion pipelines.
Conclusion
NetApp’s connector for Microsoft 365 Copilot fills a practical and pressing need: letting Copilot reason over enterprise files without forcing wholesale data migration. Its combination of item‑level ACL extraction, chunked ingestion to work around Graph limits, and containerized deployment options make it a strong candidate for enterprises that run NetApp storage and want Copilot to operate on their institutional knowledge.However, IT leaders should be pragmatic: verify deployment models (VM/GCA vs. container), validate performance claims against your own datasets and topology, and ensure governance questions — where embeddings are stored, how long OCR artifacts persist, and how permissions map into Entra/Microsoft Graph — are explicitly answered before a production roll‑out. NetApp’s public documentation and Microsoft’s architecture guidance provide the technical starting point, but enterprise risk and compliance teams will need to treat the connector as they would any system that expands the reach of AI into sensitive data estates.
Source: Windows Report NetApp Neo Connector Supercharges Microsoft 365 Copilot with External Data