Solutions Hub: DSPM, AI SPM, Agentic SPM

Manage security posture across 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 surfaces the exposures that matter, such as secrets in development environments, overexposed financial data, and top secret files a copilot can read, then guides the fix with access governance, activity monitoring, DLP, and disposition, and extends all of it to the AI models and agents now reaching the same data.

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Intuit classification challenge

Ranked #1

96.5% weighted precision and recall on a 40,000 record dataset, against 19 other vendors

Analyst recognition

A Leader in DSPM research

Named a Leader in The Forrester Wave for Sensitive Data Discovery and Classification, Q2 2026, and in DSPM evaluations from Omdia, GigaOm, and Frost & Sullivan

Posture that acts

Every risk arrives with its fix

Overexposed data, stale access, and unmanaged AI each come with the guided step that closes them

What DSPM includes 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 since moved inside that boundary, and BigID includes them natively, which changes what a DSPM purchase covers.

Findings turn into action in the same place. BigID revokes access, fixes the policy that misfired, and disposes of data where the risk is found, and it assesses access at the identity that reaches the data, whether that identity belongs to a person or an agent. Each source gets the scan depth it needs, from metadata only to a full scan, so controls that block or tokenize rest on complete reads.

Detect

Find the risk across data, AI, and agents. BigID discovers sensitive data in every store, classifies it, and flags the exposures that matter: overshared files, stale access, and unmanaged models and agents.

Prevent

Stop risk before it forms. BigID limits what employees, copilots, and agents can reach by sensitivity and permission, watches for sensitive data in AI prompts, and gives your DLP, IAM, and SIEM the context to enforce policy.

Remediate

Close the risk where it was found. BigID revokes access, fixes the policy behind a bad alert, and disposes of data you no longer need, with legal hold and downstream impact checked first.

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 those same findings.

Platform demo

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Walk the platform from discovery and classification through posture, alerts, and remediation.

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One posture loop for your data, your AI, and your agents

Data is the linchpin of safe AI use, so data security and AI security 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.

Secrets and passwords in development and test environments turn up in discovery, and BigID shows who and what can reach them and guides their removal.

Regulated financial data open to far more people than need it is ranked by exposure, and BigID right-sizes access to the people who use it.

Top secret files in a SharePoint site that Copilot can read are found before the copilot surfaces them, and BigID narrows access at the source.

Each pass through the loop finds the data, classifies it, shows who and what can reach it, acts on the risk, and keeps watching. BigID includes access governance, activity monitoring, lifecycle management, and privacy natively, and feeds classification and ownership context to the DLP, IAM, and SIEM tools you already run. Models and agents sit in the same loop as data stores, so the data question and the AI question are answered in one place.

Start here

Where security teams start with DSPM

Which risks should we fix first, and how? Secrets and passwords in development environments, regulated financial data open to the whole company, top secret files in a SharePoint site Copilot can read, each ranked and paired with the guided step that closes it. Risk prioritization → Where is our sensitive data, and can we trust the classification? 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 → How do we act on real DLP incidents instead of every alert? 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 →

Capabilities

Find the risk, fix it, and keep watching, across data, AI, and agents

Each group starts from a risk a security team already carries and ends with the action that closes it. Discovery and classification come first among the controls, because every later one depends on them.

Risk prioritization and guided fixes

Posture is about surfacing the risk that matters and showing what to do about it. BigID scores each finding on how sensitive the data is, how widely it is exposed, and who and what can reach it, then attaches the next step.

Find secrets, passwords, and keys sitting in development and test environments
Surface regulated financial data that is open to far more people than need it
Catch top secret files in a SharePoint site that Copilot can read, and right-size access before it surfaces them
Risk scoring that combines sensitivity, exposure, access, and activity
Guided remediation for every risk, from revoking access to fixing the policy at the source
A prioritized queue of findings, with duplicates and false positives filtered out before anyone triages them
Each finding names the data, its owner, who and what can reach it, and why it matters
Assign each risk to the data owner with the context needed to act
Track risk trends and closed findings over time

Discovery and classification

Every control below this one, and every tool you feed, inherits the quality of the classification. Accuracy that data owners can verify is what makes the rest of the program dependable.

2,000+ pretrained classifiers
Prompt based LLM classification for structured and unstructured data, first in the category
Agentic DSPM 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
Scaled and uncapped classification 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

BigID reads permissions metadata, attests it, watches real behavior against it, and acts when the two disagree. Agents do not hold access of their own: they reach data through the identities associated with them, so that identity is where the control sits.

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 alerts, without the noise

BigID sits above the DLP tools you already run as the policy engine: every violation is validated against what the data actually is, thousands of alerts become a prioritized queue, and every remediation sharpens the next policy decision.

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 most direct way to shrink a blast radius is to hold less data. Guardrails for legal hold and downstream impact run before anything is disposed of.

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, applied to models and agents. 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
Trace how sensitive data flows into AI pipelines, RAG indexes, and training sets
Right-size what copilots and assistants can index before they surface it

Third party validation

Named a Leader in all DSPM research

Analyst recognition

A Leader in The Forrester Wave™: Sensitive Data Discovery And Classification Solutions, Q2 2026, with the highest possible score in eleven criteria
Ranked #1 in Intuit's 20 vendor data classification challenge, at 96.5% weighted precision and recall
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 →

FAQ

How BigID fits alongside the tools you run today

How does BigID work with the DLP we already run?

It sits above your DLP tools as the policy engine. BigID 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 spend your time on real incidents.

Can our access reviews stay where they are?

Yes, and they can move when you are ready. BigID runs permission review and entitlement attestation natively, using the same classification that found the data, 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.

What does BigID do beyond finding the data?

BigID acts on a finding where it was produced: revoke the access, retire the unused entitlement, apply the right protection to the file, dispose of the store, with legal hold and downstream impact checked first. The policy that found the risk is the policy that fixes it.

What is data security posture management (DSPM)?

DSPM finds sensitive data wherever it lives, assesses the risk around it, and drives the fix. It answers where the data is, how it is classified, who and what can reach it, and what to do about the exposure. BigID includes classification, access governance, activity monitoring, data loss prevention, lifecycle management, and privacy natively, on one platform, starting from data discovery and classification and data access governance.

What are AI SPM, agentic SPM, and agentic DSPM?

They apply the same posture questions to AI models and to the agents acting on data. AI security posture management (AI SPM) discovers sanctioned and unsanctioned models, shows what data each one can reach, and monitors what employees share with AI prompts. Agentic SPM extends that to agents, which reach data through the identities they run under, so BigID governs access at that identity. Agentic DSPM is the other direction: agents doing part of the posture work, such as checking classification accuracy and validating DLP violations before anyone triages them. The findings feed AI governance and AI assistant readiness.

How does DSPM support GDPR, CCPA, and other regulations?

Regulations start with knowing which personal and regulated data you hold and where. BigID classifies personal, financial, and health data across structured and unstructured sources, and the same findings feed privacy and compliance automation, retention policy through data lifecycle management, and access reviews, so GDPR, CCPA, and HIPAA work all draw on one set of findings.

Which risks should we fix first?

Start where sensitive data, broad exposure, and real access meet. BigID scores each finding on how sensitive the data is, how widely it is exposed, who and what can reach it, and whether anyone uses it, then attaches the guided step that closes it, so teams begin with the exposure that matters most.

How does BigID cut the noise out of security alerts?

It validates each alert against what the data actually is. BigID ingests violations from every DLP tool you run, correlates each with its classification, marks it true or false positive with a confidence score, and turns thousands of alerts into a prioritized incident queue with platform specific steps to fix the policy behind the noise.

What kinds of risk does DSPM surface?

Exposures that matter to a security team, found where they sit. Examples include secrets and passwords in development environments, regulated financial data that is overexposed, and top secret files in a SharePoint site that Copilot can read. BigID shows the data, the people and agents who can reach it, and the steps to right-size access or remove it.

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