Solution hub: DSPM, AI SPM, Agentic SPM

Posture management for your Data, your AI, and the Agents acting on both

DSPM began as data risk discovery: find the sensitive data, assess the risk around it. BigID goes further: giving teams security controls to manage that risk, from access governance and activity monitoring through egress and disposition, and extends all of it to the AI models and agents now reaching the same data.

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Classifiers

AI-Powered

LLM classifiers, with independent lab verified 97% accuracy.

Category first

Agentic automation

and analysis, including classification that checks its own work

Architecture

One Inventory

Data, AI, and agentic assets, all governed by one policy model

Start here

Five questions, and where BigID answers each one

Where is our sensitive data, and can we trust the labels? 2,000+ pretrained classifiers, prompt based LLM classification for structured and unstructured data, and an accuracy review your data owners can run themselves. Discovery and classification → Who can reach it, and who actually does? Permission review and entitlement attestation, behavior watched against policy, and revocation or right-sizing at the point of the finding, for human identities and for the agents running under them. Access and activity → Why is our DLP generating so much noise? Every violation from every DLP tool in one queue, validated true or false with a confidence score, and platform specific steps to fix the policy that misfired. Data loss prevention → What can we delete without breaking something downstream? ROT detection, sandboxed review before anything moves, soft and hard delete, with legal hold and downstream impact checked first. Lifecycle management → Which models and agents are touching all of it? Discovery of sanctioned and unsanctioned models and agents, what data each one reaches through the identity it runs under, and governance over how agents use data and call each other. AI and agentic posture →

Where the category is now

DSPM kept its name and outgrew its definition

Organizations adopt DSPM to identify and remediate data risk, whether the driver is security, compliance, or AI. Access governance, activity monitoring, loss prevention, lifecycle, and privacy management have all since moved inside that boundary, and the platforms that went furthest include them outright rather than integrating out to them, which changes what you are actually buying.

Included natively

DAG, DAM, DLM, and DPM. The control runs in the same console as the finding, against the same inventory that produced it.

Kept and strengthened

Your DLP, IAM, and SIEM keep their enforcement points and get the classification, ownership, and access context their policies run on.

Newly covered

AI and agentic assets under the same posture model, because data is what makes AI use safe or unsafe.

Data security and AI security both start with the same question

Data is the linchpin of safe AI use, so the two disciplines open on the same ground: what is in this data, who can reach it, and what changes when a model or an agent reaches it instead of a person.

An agent never holds access of its own. It reaches data through the identity it runs under, inherits everything that account can see, and acts on it at machine speed.

A prompt carries regulated data to a third party model, through a channel your DLP never had a policy for.

A copilot indexes a share nobody has reviewed in years, and surfaces it to everyone who can ask.

BigID includes access governance, activity monitoring, lifecycle, and privacy natively rather than integrating out to them, and feeds classification and ownership context to the enforcement points you already run. Coverage extends past data stores to the models and agents reaching them, on one inventory and one policy model, which is what lets the data question and the AI question be answered in the same place.

See what BigID can do

Watch it work

BigID Platform Demo: DSPM + DAG + DAM for Structured & Unstructured Data

A full walkthrough of the platform: discovery and classification across structured and unstructured data, then access governance and activity monitoring running against that same inventory.

Platform demo

In this hub

Capabilities

Everything BigID does across the five groups

Grouped the way a security team scopes the work, starting with discovery and classification because everything after it depends on getting that right.

Discovery and classification

Every control below this one, and every tool you feed, inherits whatever classification gets wrong. Accuracy is the dependency nobody audits until an access decision is already made on it.

2,000+ pretrained classifiers, more than any other vendor
Prompt based LLM classification for structured and unstructured data, first in the category
Agentic accuracy supervision, so classification checks its own work
In-product accuracy review for the humans who own the taxonomy
Advanced sensitivity classification
AI based categorization by business taxonomy or label
Scaled and uncapped labeling across structured and unstructured data
Find stale, duplicate, ROT, and out of compliance data
Analyze impact radius after a breach by tracing data exfiltration

Access governance and activity

Reading permissions metadata is the easy half. BigID attests it, watches real behavior against it, and acts when the two disagree. Agents get no access of their own, they reach data through the identities associated with them, so that identity is where the control has to sit.

Manage access permissions and usage against policy and unusual behavior
Run regular permission reviews and entitlement attestation
Revoke and right-size access quickly on policy violation
Retire stale data through retention policy, where nothing has touched it in a defined window
Retire stale access through access certification, where an entitlement has gone unused
Breach investigation: trace data and access exposure by account and identity, and bound the blast radius
Limit AI access to data by sensitivity and by the employee's own permissions
Detect problematic sharing of data inside AI prompts
Extend the same control to non-human agents at the identity each one runs under

Data loss prevention

Legacy DLP runs on broad regex patterns and buries real risk under false positives. BigID sits above the tools you already run as the policy engine: every violation validated against what the data actually is, and every remediation making the next policy decision sharper.

Ingest violations from every DLP tool you run into one unified queue
Correlate each violation against what BigID already knows about the data behind it
Validate true and false positives, each with a confidence score
Alert detail carrying user identity, sensitivity classification, affected objects, and business risk level
Platform specific remediation steps, down to which classifiers to add or remove from a Purview policy
See which DLP policies are failing, across every channel, in one place
Cut thousands of alerts down to a prioritized incident queue

Data lifecycle management

The cheapest way to shrink a blast radius is to hold less data. Disposition is also the easiest place to break a downstream system, which is why the guardrails matter more than the delete.

Detect and dispose of redundant, obsolete, and trivial data
Easy policy and query builder with advanced targeting
Simplified, sandboxed review of the target data before anything moves
Integrated move, tombstoning, and restore
Soft delete for archive and hard delete for purge
Native guardrails for safeguarded disposition, including legal hold and downstream impact

AI and agentic posture

The same posture questions, asked of an asset class with no owner and no change control. What models exist, what agents run, which identities they reach data through, and who approved any of it.

Monitor what data employees share with AI prompts
Discover sanctioned and unsanctioned models and agents
Find AI agents and keep monitoring them as they change
Govern how agents use data and how they interact with one another

Third party validation

Named a Leader in all DSPM research

Analyst recognition

Leader placements across the Omdia DSPM Universe, CB Insights, TAG, GigaOm, and Frost & Sullivan
2025 Company of the Year for AI Governance, Frost & Sullivan
Named in Gartner's 2025 Market Guides for both DSPM and AI TRiSM
Named a Leader in all Privacy Management evaluations, including the Forrester Privacy Management Wave and the IDC Privacy Compliance MarketScape
Named a Leader across four GigaOm evaluations: DSPM, data security platforms, unstructured data management, and data access governance
Represented more than 30 times across Gartner's 2025 Hype Cycles for security, privacy, and AI SPM

In a customer's words

“BigID gives me better visibility into sensitive data, helps prioritize security protections, reduces attack surfaces, strengthens compliance, and increases operational efficiency overall, a strategic pillar of our AI-First Cybersecurity Transformation.”

CISO, global healthcare company

“We needed to automate processes and data management across systems for the data of a few million customers… BigID was the one solution that did this in the most efficient and sophisticated way, and had more use cases we could add on moving forward.”

Chief Privacy Officer, global telecoms company

Read how Fiserv runs it as one control plane →

Before you scope it

What teams ask before they start

Do we have to replace our DLP?

No, and the design assumes you will not. BigID sits above the DLP tools you already run: it ingests their violations, validates each one against what the data actually is, and hands back platform specific steps to fix the policy that misfired. You keep the enforcement point and lose the false positive pile.

Do our access reviews have to move?

Only if you want them to. BigID runs permission review and entitlement attestation natively against the same inventory, for human identities and for the agents running under them, or feeds ownership and sensitivity into the identity process you already have. Either way the reviewer sees what the data actually is, not just a list of who can reach it.

How is this different from a scanner?

A scanner hands you a finding. BigID acts on it where it was produced: revoke the access, retire the unused entitlement, label the file, dispose of the store, with legal hold and downstream impact checked first. One inventory means the policy that found it is the policy that fixes it.

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