Securiti

What do you like best about the product?

I use Securiti for sensitive data discovery and data privacy management across cloud environments. I like how it automates the process of finding shadow data and sensitive PII, reducing manual compliance auditing efforts and preventing potential data privacy risks. The automated AI-driven data intelligence catalog is impressive as it dynamically classifies sensitive assets without manual tagging. I find the unified dashboard exceptional for providing real-time visibility into compliance posture across multi-cloud integrations, which saves hours during audits and ensures prompt remediation of risks. Additionally, integrating it with tools like AWS S3, Snowflake, Jira, and Slack enhances its functionality with real-time security alerts.

What do you dislike about the product?

I find the initial setup and rule configuration to have a steep learning curve, and we feel that the platform pricing can be high for smaller deployments.

What problems is the product solving and how is that benefiting you?

I use Securiti to automate the discovery of shadow data, reducing my compliance audit efforts and preventing privacy risks. The AI-driven catalog helps me classify sensitive assets dynamically, and the unified dashboard provides me real-time compliance visibility, saving me hours during audits and ensuring prompt risk remediation.

What do you like best about the product?

What I value most about Securiti is how it serves as a reliable safety checkpoint for all our customer and employee survey data, especially after the scary close call we had while still using OneTrust. Back then, our old tool failed to detect customer network account IDs buried in open-ended feedback, and I almost uploaded unredacted survey data to Galileo AI for sentiment analysis. That incident made me realize manual reviews and basic scanners could never fully eliminate human error. Securiti’s automated PII discovery and bulk masking solve this pain point perfectly. Every time I import survey CSV files, it rapidly scans thousands of responses, picks up emails, phone numbers and our unique network account identifiers, and redacts sensitive information in batches. I no longer need to comb through each comment line by line. The permanent audit trail is another standout feature. Every file upload, scan and masking action gets timestamped automatically. When our management asked for compliance proof last quarter, I exported organized logs in minutes instead of scrambling to compile disjointed screenshots and spreadsheets. I can also build custom governance rules to block unsanitized survey data from being shared with Pokee AI and other external AI tools. Best of all, the platform does not require deep compliance knowledge to operate. Our company has no dedicated privacy specialist, and I handle all data governance work independently. Securiti balances powerful privacy controls with approachable operation, letting our lean CX team leverage AI survey analysis while staying protected against CCPA violations.

What do you dislike about the product?

First, the native file import options lack flexible formatting support for the CSV exports I pull from our survey tools. Every time I download survey responses to sanitize them before sending to Galileo AI or Pokee AI, certain custom survey column layouts cause inconsistent scanning results. Earlier this quarter, I ran a scan on our employee engagement poll data, and free-text comment columns were partially ignored because of special line breaks within open-ended feedback. I had to reformat and reupload the file twice to get accurate PII detection, eating up valuable time I planned to spend analyzing feedback trends. The reporting module is also oriented toward large enterprise compliance teams. The default audit logs include extensive technical metadata that our leadership does not need to review. There is no simple template to generate streamlined CX-focused compliance summaries. When executives ask for high-level proof we are protecting survey participant data, I have to manually filter, copy and reorganize log entries in separate spreadsheets instead of exporting a ready-to-share overview directly from Securiti. One major area for improvement is more granular rule-building for PII classification. Right now, the platform’s detection rules are fairly universal, and I cannot easily create custom labels specific to our industry. Our survey respondents frequently share network service account IDs, which qualify as sensitive internal identifiers alongside standard emails and phone numbers. Securiti does not let me quickly train the model to consistently recognize these account numbers without building complex custom detection scripts. Since we don’t have a dedicated compliance engineer on staff, configuring those advanced rules is intimidating. I would also welcome better workflow automation for repeated survey tasks. Every quarterly feedback campaign follows the same process: import survey results, mask PII, generate audit records, and export sanitized files for AI analysis. Today, every single step must be triggered manually. If I could save reusable workflow templates for customer surveys and internal employee polls, I would avoid repeating the same configuration steps every cycle. The initial setup of Securiti was a mixed experience. Basic account activation and exploring standard PII scanning workflows were straightforward to complete, but tailoring the platform to fit our CX survey workflow became far more complex without dedicated compliance engineers on our team. I struggled with file import configuration right away. Our survey exports contain line breaks inside free-text comment columns, which caused inconsistent parsing during scans. We also lacked native integrations to connect Securiti with Galileo AI and Pokee AI, so there was no streamlined pipeline to configure during setup; I had to plan entirely manual file export and upload workflows from scratch.

What problems is the product solving and how is that benefiting you?

Before adopting Securiti, our survey data workflow carried serious hidden compliance risks. We relied on OneTrust paired with manual spreadsheet edits to strip personal information from customer satisfaction polls and internal staff surveys. This workflow was slow and unreliable. During our mid-year customer feedback campaign, the old scanner missed dozens of network service account IDs within open-ended comments. I nearly sent raw unprocessed data to Galileo AI, which would have exposed participant private information and triggered regulatory risks. Securiti directly fixes this vulnerability by automating PII detection and bulk masking for every survey dataset. It also maintains complete audit records for all data processing activities and enforces consistent data retention policies to stop us from hoarding outdated feedback files indefinitely. All these capabilities remove hours of tedious manual checking from my weekly workload. Now I can safely pass sanitized survey data to Pokee AI and gjalla to analyze customer experience trends and draft CX reports. Instead of spending most of my time worrying about accidental data leaks, I can focus on interpreting feedback and identifying opportunities to improve our network support services. For our small team without compliance support, Securiti turns risky, error-prone data handling into a standardized, repeatable process and drastically reduces the chance of privacy violations.

What do you like best about the product?

I really like the depth of Securiti's data discovery and classification features, especially its ability to identify sensitive information across cloud, SaaS, and unstructured data sources. The AI-powered classification and contextual risk insights make it so much easier for me to prioritize what actually needs attention. I also appreciate the data lineage and AI governance features that add useful visibility as more data gets used with AI. Additionally, the initial setup was very easy.

What do you dislike about the product?

The biggest area for improvement is the learning curve. Securiti covers so many areas across data security, governance, compliance, and AI that it can take some time to understand how everything fits together. I’d also like to see even more streamlined workflows and clearer prioritization of alerts, so teams can quickly focus on the highest risk issues without getting overwhelmed by the platform’s breadth.

What problems is the product solving and how is that benefiting you?

I use Securiti to discover and classify sensitive data in cloud and SaaS environments, tracking data access and governance. It simplifies prioritizing security issues and AI risks, though setup can be complex due to its broad features.

What do you like best about the product?

What stands out most about securiti is its unified data command center, which automatically discovers and classifies sensitive subscriber data and media assets across hybrid multicloud environments. It makes maintaining global privacy compliance and governing sensitive AI data flows remarkably seamless without slowing down our streaming operations.

What do you dislike about the product?

The extensive feature set creates a steep learning curve, making the initial admin setup and policy configuration feel complex. Additionally, automated deep scanning jobs on massive data lakes can occasionally consume significant cloud compute resources during peak OTT usage hours.

What problems is the product solving and how is that benefiting you?

Securiti solves the problem of fragmented subscriber data, shadow AI usage, and complex global compliance requirements across hybrid clouds. It benefits us by automating privacy workflows and data governance, allowing our team to focus on expanding OTT streaming services without worrying about regulatory fines or data leaks.

What do you like best about the product?

What really sets Securiti apart is how it solves data fragmentation by unifying data security, privacy, and governance into a single Data Command Center. Instead of forcing teams to stitch together separate tools for data discovery, DSAR compliance, access control, and AI governance, Securiti continuously maps and contextualizes sensitive data across complex multi-cloud environments allowing organizations to automate heavy compliance workflows and protect data fed into AI models without burning out engineering teams on manual tasks.

What do you dislike about the product?

The biggest drawback of Securiti is its complexity and the steep learning curve during initial setup. Because it aims to cover everything from privacy and governance to security posture across multi-cloud environments, getting it properly configured and fine-tuned especially in a way that avoids alert fatigue can take significant time and real engineering effort. On top of that, its enterprise-level pricing can make it cost-prohibitive for smaller teams. Finally, performance and overall usability depend heavily on pre-built connectors, so if you’re running niche or legacy data systems, what should be seamless integration can quickly turn into a manual, time-consuming headache.

What problems is the product solving and how is that benefiting you?

At its core, Securiti helps cut through the chaos of data sprawl and fragmentation especially the danger of shadow data hidden across multi-cloud environments, the burden of manual privacy compliance (like DSARs and GDPR requirements), and the risk of sensitive information leaking into AI and LLM pipelines. For organizations, the main payoff is operational efficiency and risk reduction: it can replace half a dozen point solutions with a single "Data Command Center," saving engineering teams hundreds of hours otherwise spent on manual data mapping, automating key compliance workflows, and giving leadership more confidence to adopt modern AI tools without accidentally exposing sensitive customer or business data.