Bold vs. Orion Security for Endpoint Data Loss Prevention

Bold vs. Orion Security: key takeaways

Bold and Orion Security agree that DLP policies are the problem and that AI should replace them. The main differences have to do with where to operate to watch data move.

• Coverage model: Orion reaches data through integrations, connecting to roughly two dozen services including Google Drive, SharePoint, OneDrive, GitHub, Salesforce, Slack, Teams, Microsoft 365, and Gmail, with a browser extension and an endpoint sensor alongside them. Bold installs on the endpoint and treats the device as the whole architecture.
• Where the decision is made: Orion's AI agents evaluate data movement across classification, lineage, identity, environment, and external relations, and reach a verdict in its cloud. Bold runs small language models on the device, so classification and enforcement happen locally at the moment of the action.
• What each one sees best: Orion sees data moving between connected cloud applications, including activity on devices it has no agent on. Bold sees local files, clipboard activity, USB writes, printing, AirDrop, and desktop applications that encrypt their own traffic, none of which touch an API or a browser tab.
• Offline and untrusted networks: Bold classifies and enforces with no connection. Any cloud-evaluated architecture should be tested on a disconnected laptop.
• Scope: Orion is a data loss prevention product. Bold covers endpoint DLP, insider risk management, and AI usage control from one agent.

Use cases covered here: endpoint data loss prevention, insider risk management, and AI usage control.

Orion Security background

Orion Security was founded in 2024 by Nitay Milner, who is chief executive, and Jonathan Kreiner, chief technology officer. Milner was a product leader at Epsagon, the observability company acquired by Cisco, and Kreiner led application security work at WalkMe. The company operates from New York with research and development in Tel Aviv.

Orion emerged from stealth in 2025 with a $6 million seed round led by Pico Partners and FXP with participation from Underscore VC, then raised a $32 million Series A in February 2026 led by Norwest with participation from IBM and existing investors PICO Venture Partners and Lama Partners, bringing total funding to $38 million. It says it has enterprise customers in finance, healthcare, and technology, and publishes named testimonials from the CISOs of Omegapoint and SHL.

At one point, its homepage headline read "DLP that understands your DNA," with the line that Orion maps, learns, and monitors your business workflows with the power of AI. The company describes the product as autonomous and context-aware, using proprietary AI agents that evaluate every data trace across classification, lineage, identity, environment, and external relations before deciding whether something is an incident. Milner's public framing is that better policies were never the answer, and that the policy model itself is the flaw in DLP.

We agree with that diagnosis at the highest level, as do all next-gen DLP providers. Orion is not a legacy vendor with AI bolted on. It is a company that rebuilt the category around the same objection we started from, and it has built real breadth across cloud and SaaS. But is that where the biggest data risks lie?

Why DLP is being rebuilt, and what that leaves unsolved

Legacy DLP identifies sensitive data by pattern. Regular expressions, keyword dictionaries, and exact data matching work for credit card numbers and national identifiers and fail for source code, pricing models, pre-release designs, and board material. Worse, they put the burden on the security team: every new data type, workflow, and AI tool needs another rule, and the rules never catch up. That is the failure both Orion and Bold were founded to fix.

Replacing policies with AI is the easy half of the agreement. The harder question is where the AI should sit, and that question only matters because of where data actually moves now. A sales operations analyst exports a customer list from Salesforce, opens it in Excel, trims the columns, saves it locally, renames it, and drops it onto a USB stick or into a desktop AI assistant. The first step crosses an API. The rest never does.

The same gap appears with AI. Browser-based chatbots are visible to a browser extension. Desktop AI applications that encrypt their own traffic, AI browsers, and local coding assistants reading a repository are not, unless something is running on the device with the privileges to see them.

So the evaluation comes down to: what does each product see, where does it decide, and what can it stop. The three use cases in this comparison:

Endpoint data loss prevention: stopping sensitive data from leaving a managed device through web uploads, email, personal cloud accounts, removable media, printing, clipboard, and screen capture.

Insider risk management: identifying when someone is collecting, obfuscating, or moving data they have access to but no business reason to take, and producing evidence Legal and HR can act on.

AI usage control: seeing which AI tools, AI browsers, and coding assistants run on each device, what data goes into them, and enforcing policy without blocking the tools people need.

Bold vs. Orion Security: key differences

The endpoint is the architecture, not one sensor among several

Bold installs on the device and sees what happens there directly: local files, clipboard, USB writes, printing, AirDrop, Bluetooth, git pushes, and desktop applications including AI assistants that encrypt their own traffic. None of that activity crosses an API connector or a browser tab, which means integration-led coverage reaches it only through whatever its endpoint sensor collects.

Orion's strength is the opposite shape. Its connectors cover roughly two dozen services and give it visibility into SaaS-to-SaaS movement, cloud repositories, and email, including on devices with no agent installed. If your risk picture is dominated by sanctioned cloud applications and contractor machines you will never manage, that reach is real and Bold does not have it.

The models run on the device, so the verdict arrives before the action completes

Bold runs small language models locally, using the laptop's own CPU and memory. Classification, context, and the enforcement decision happen in the same place as the file, the paste, or the prompt. There is no round trip to a vendor cloud, no per-event inference cost, and classification carries no cloud bill.

Orion's AI agents assemble a full picture across several dimensions before making a determination, and that assembly happens in its cloud. For an accuracy-first product that is a sound trade, and it is why Orion can reason about relationships between systems that a single device cannot see. It also means the decision arrives from elsewhere.

Enforcement that holds when the network does not

Disconnect a Bold-protected laptop and it keeps classifying and enforcing. The same is true on untrusted networks and inside applications that encrypt their own traffic.

This is two minutes of testing. Take a laptop off the network, open a sensitive engineering document, copy a section into a personal webmail draft, and try to write the original to a USB drive. Run it on both products.

Coaching the person, not just catching the flow

Bold's enforcement is graduated. It coaches when intent is unclear, redirects to a safe alternative such as a corporate AI account instead of a personal one, and blocks on clear exfiltration. About 85% of users comply when they are coached, which means most risky actions end without an incident, a ticket, or an investigation for anyone to run.

That only works if the decision is in front of the action. A product that evaluates data flows and surfaces risk is doing a different job, and a valuable one, but the person has already clicked by the time it reports.

Three use cases from one agent

Orion is a data loss prevention product and positions itself that way.

Bold covers data loss prevention, insider risk management, and AI usage control from one agent and one shared context. The same classification that decides whether an upload is sensitive gives the insider risk case its data dimension, so a risk score reflects both what someone did and what data was involved. For a small security team, that is the difference between one deployment and three.

Classification happens without sending content off the device

Because classification runs locally, no file content, prompt text, or screen content leaves for analysis. Encrypted evidence is written to your own cloud tenant under your own key, Bold receives metadata only, and that metadata can be masked. Monitoring is scoped by provenance, so personal data moving from a personal source to a personal destination can be left unmonitored.

An integration-led architecture reads content from the systems it connects to, by design. Ask both vendors the same three questions: what content leaves, where it is stored, and under whose key.

Bold vs. Orion Security comparison

Bold channel and operating system coverage

Comparison tables are easy to write and hard to verify, so here is Bold's coverage by channel and operating system, including the channels where Bold monitors today rather than blocks. Ask any vendor you are evaluating, including us, for the same table.

Key Orion Security features

The features below are described as Orion documents them on its own site and in its public materials.

Indicators of Leakage

Orion's framing for the signals that indicate data is leaving in a way it should not, used in place of written policies.

Orion Data Graph

A single record of data movement across the organization, assembled from the systems Orion connects to.

Data DNA

A learned model of how data normally moves through the business, used to separate secured flows from risky flows and anomalies.

Orion Hunter

Investigation tooling for catching deviations and insider activity, with filtering by department, data type, source, destination, and timeline.

AI agents and classification

Specialized agents evaluate each data trace across classification, lineage, identity, environment, and external relations, with classification handled by the company's own models rather than pattern rules.

Connectors, browser extension, and endpoint sensor

Coverage is assembled from integrations with services including Google Drive, SharePoint, OneDrive, GitHub, GitLab, Bitbucket, Microsoft 365, Google Workspace, Salesforce, Confluence, Slack, Teams, Outlook, and Gmail, alongside a browser extension and an endpoint sensor.

Our honest take: connectors reach wide, the device runs deep

Orion is a real product with a solid thesis, and the parts of it we would not try to argue with are the parts we do not do. Connectors see things an endpoint agent cannot: a file shared from one SaaS application to another, a repository exposed to the wrong group, activity on a contractor's unmanaged laptop. If that is the shape of your risk, Orion covers it and we do not. Deployment is also easier when it starts with API connections rather than an agent rollout, and for a small team that matters.

Where we think the architecture favors Bold is the part of the day that never crosses a connector. This is crucial because work is happening on the endpoint. The export, the local edit, the rename, the USB write, the paste into a desktop AI assistant, the git push, the print. That activity is most of what an insider actually does, and seeing it requires being on the device with the privileges to watch it, not reaching toward the device from outside.

The test that separates us is simple: pick the ten things your riskiest employee could do this afternoon, and count how many of them touch an API.

Orion Security alternatives

Bold: real-time data protection for the modern endpoint. Purpose-built AI models run locally to classify data by meaning, read the context around every action, and prevent data loss at the moment it happens, with full coverage offline. Endpoint DLP, insider risk, and AI usage control from one agent.

Cyberhaven: the most established of the modern DLP challengers, built around data lineage, with DSPM for cloud and SaaS data at rest. Broader surface area, with analysis running in its cloud.

Cyera: agentless data security posture management across cloud, SaaS, and on-premises stores, with DLP and endpoint capability added by acquisition.

MIND: data loss prevention focused on discovery and classification across SaaS and endpoints, frequently shortlisted by teams replacing legacy DLP.

Microsoft Purview: the broadest labeling and compliance footprint, strongest for organizations deep in Microsoft 365 that need regulatory reporting. Usually paired with endpoint enforcement rather than replaced by it.

Netskope: strong cloud and web enforcement through a service that inspects routed traffic. Covers the network layer well; data at rest on the device sits outside that inspection.

Forcepoint: mature legacy DLP with deep regulatory templates and channel coverage, chosen by organizations with established policy libraries and the staff to tune them.

The bottom line

One detail worth knowing: IBM participated in Orion's Series A alongside Norwest. That is a distribution signal as much as a funding one, and it suggests the product will show up more often inside larger enterprise conversations than its size would predict.

Orion Security reaches data through the systems it connects to and decides in its cloud. Bold sits on the device and decides there, in the moment, connected or not.

• For endpoint data loss prevention: Bold enforces on local files, clipboard, USB, printing, and desktop applications at the moment of action, offline included. Orion covers data movement across connected SaaS and cloud services, plus browser and endpoint sensors.
• For insider risk management: Bold joins behavior to on-device classification, so a risk score carries a data dimension. Orion's Data DNA and Hunter tooling model normal flows and surface deviations across connected systems.
• For AI usage control: Bold sees every AI tool on the device, including desktop AI applications and local coding assistants, and attributes actions to a person or to software running on its own. Orion covers AI tools as a monitored surface within its data flow model.
• For SaaS to SaaS movement and unmanaged devices: Orion covers it, Bold does not.
• For regulated environments: Bold keeps file content on the device and writes encrypted evidence to your tenant under your key, which is a different answer to a works council or residency review than cloud-side analysis.

Bold vs. Orion Security FAQs

What is Orion Security?

Orion Security is an AI-native data loss prevention company founded in 2024 by Nitay Milner and Jonathan Kreiner, based in New York with research and development in Tel Aviv. It has raised $38 million, including a $32 million Series A led by Norwest with IBM participating in February 2026, and sells an autonomous, context-aware DLP product that replaces written policies with AI agents.

What is the main difference between Bold and Orion?

Where each one stands. Orion reaches data through integrations with cloud and SaaS services and decides in its cloud. Bold runs on the endpoint and decides there, which covers activity that never crosses an API or a browser tab.

Does Orion have an endpoint agent?

Yes, Orion has an endpoint sensor alongside its connectors and browser extension. The difference is architectural weight: for Orion the endpoint is one input among several, and for Bold it is the whole product.

Does Orion work offline?

Worth testing rather than assuming for any product whose verdicts are evaluated in a vendor cloud. Bold classifies and enforces with no connection, because the models are on the device.

Does Bold cover SaaS to SaaS data movement?

No. If a file moves from one cloud application to another without touching a managed device, that is outside what an endpoint agent can see, and it is a genuine reason to consider Orion or to run a connector-based product alongside Bold.

Which is better for AI usage control?

Bold sees every AI tool running on the device, including desktop AI applications, AI browsers, and local coding assistants, and attributes each action to a person or to software acting on its own. Orion covers AI tool usage within its data flow model, which captures what crosses its connectors and browser extension.

Do either of them require writing DLP policies?

Neither is policy-first, which is one of the few things the two companies fully agree on. Bold classifies by meaning on day one with no rules to write. Orion replaces the policy model with contextual AI verdicts, while keeping a policy layer for the controls compliance teams require.

How long does each take to deploy?

Bold installs in minutes and classifies immediately, with no baseline period and no tuning. Orion's deployment begins with connecting services, which is fast for the SaaS surface, with the browser extension and endpoint sensor rolled out separately.

Sources: Orion seed round coverage, Series A coverage in Globes, Orion Security homepage, Orion product page, CEO interview

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