Rehan Jalil is the CEO of Securiti.AI, Enterprise Advisor at Mayfield Fund and an investor and mentor to many Silicon Valley startups. He was the SVP and GM for Cloud Security at Symantec.
Securiti AI is an enterprise-grade centralized platform that allows the secure use of information and AI – and the pioneer of the Data+AI Command Center. Corporations depend on Securiti for his or her data security, privacy, governance and compliance. Securiti has been recognized with quite a few industry and analyst awards, and most recently was acknowledged by Gartner Peer Insights as Customers’ Selection for DSPM, and by GigaOm because the top-rated vendor for DSPM.
Are you able to elaborate on the vision behind Securiti AI’s Data Command Center and the way it differentiates from other data management platforms available in the market?
Our vision with the Data Command Center is simple: we aim to empower organizations to completely leverage their data assets without compromising privacy, security or compliance. That is achieved by robotically scanning a corporation’s data landscape (SaaS, IaaS, cloud data lakes and warehouses, etc.) and getting granular insights into all of the sensitive information and AI systems. These insights, captured in a novel real-time knowledge graph, are used to implement privacy and security controls and ensure compliance with global data regulations. This platform is especially useful in developing modern generative AI systems, which feed on data – especially unstructured data. Historically, organizations have relied on a series of fragmented tools to deal with their data obligations, which has been costly and complicated. Securiti’s unified platform increases efficiency, reduces costs, mitigates risks and enables the secure use of information and AI.
What were the important thing challenges you faced while launching Securiti in 2019, and the way did your experience at Symantec shape your approach?
Considered one of the challenges we faced launching Securiti was running into the Covid epidemic just six months after launching the corporate. Within the early days of launching an organization, gaining customers and early revenue is essential. We had quite a lot of momentum, including early customer traction and winning the RSAC 2020 Most Progressive Startup. Per week after we won the RSA accolade, the world shut down and we entered an uncertain economic climate. Through my experience with Symantec and former firms, I used to be very accustomed to working with the most important global organizations on their complex security needs. As a team, we now have also been through economic downturns prior to now. This experience gave us the arrogance to stick with our strategy, proceed to take a position in solving real problems large enterprise organizations face, and patiently wait for the markets to return to a more normal state.
How does Securiti AI make sure the security of sensitive data across hybrid multicloud environments?
Securing sensitive data across complex hybrid multicloud environments demands a holistic approach. Securiti uses advanced technology to robotically discover and classify data across a corporation’s entire data landscape, akin to SaaS, IaaS, data lakes, warehouses, and on-premises systems including each structured and unstructured data. Securiti further enriches this information with deep contextual insights constructing a real-time knowledge graph, including whom the information belongs to, access entitlements, what regulations apply, where the information is situated and more. This foundation is critical for automating precise controls to safeguard sensitive information and comply with relevant regulations. For instance, the platform automates privacy obligations akin to data mapping, data subject rights requests and assessments. It also addresses data security obligations akin to data access intelligence and governance, data security posture management, data minimization and breach management. Of keen interest currently is governing unstructured data and the secure development of AI systems, including identifying shadow AI, ensuring sensitive data just isn’t feeding AI models, cataloging and monitoring risks of AI systems, and enforcing controls with LLM firewalls to guard AI systems from misuse or abuse. Our Data Command Center provides unparalleled visibility and control enabling the secure use of information and AI.
With the increasing complexity of information privacy regulations, how does Securiti AI help organizations stay compliant and manage privacy obligations effectively?
Navigating the complex web of information privacy regulations might be daunting. Recent laws is coming at a rapid pace – just like the EU AI Act, the White House AI Executive Order and California Bill 1047 hitting inside a matter of months. Enterprises have latest requirements to contemplate each day, while also adhering to frameworks akin to NIST’s AI Risk Management and Singapore’s Model AI Governance. Securiti has a dedicated research team that stays abreast of all the newest regulations and builds this information into our Data Command Center. This provides organizations with real-time context to focus on potential risks together with built-in templates to automate compliance with the newest regulations. Securiti’s Data Command Center automates lots of probably the most time-consuming and complex tasks related to privacy compliance including data mapping, privacy impact assessments, data subject rights requests, cross-border transfers, breach management and consent management.
Are you able to discuss the role of AI in Securiti’s platform and the way it enhances data security and governance?
Securiti uses advanced techniques harnessing AI and ML to offer increased accuracy in data discovery and classification. These techniques significantly reduce false positives, and augment detection of sensitive content in difficult datasets like unstructured data, images and video. Along with leveraging AI within the platform, Securiti’s Data Command Center can be critical to helping organizations govern and manage their AI ecosystems. A part of this includes securely processing large unstructured and structured datasets while ensuring that sensitive or misinformation just isn’t fueling AI models. Moreover, there’s an enormous call to safeguard privacy and data access entitlements and protect system-critical AI models from things like prompt injection and data exfiltration. Putting comprehensive controls and guardrails in place around AI systems enables organizations to embrace innovation safely.
How does Securiti’s LLM Firewall work, and what advantages does it offer in securing GenAI applications?
Our context-aware LLM Firewall has develop into a key constructing block in our security stack. For a transient overview, the LLM firewall is supplied with advanced language processing capabilities, meaning it understands user prompts in multiple languages, analyzes multimedia content, and provides robust protection against quite a lot of threats like data leakage, prompt injections and harmful content. Securiti’s LLM Firewalls are unique, in that they’re context aware – having real-time understanding of sensitive content and the context around data, akin to access entitlements – providing continuous monitoring and protection based on real-time insights into the information landscape. Securiti’s firewalls are also unique in that they inspect three different points within the AI pipeline, including prompt firewall (between the user prompt and the LLM model, protecting against malicious attacks), the retrieval firewall (between the LLM model and the vector data base, monitoring what data is being fetched for the response) and the response firewall (between the LLM model and the user prompt, ensuring appropriate responses are being issued based on corporate policies). These provide comprehensive real-time controls to safeguard AI systems. All these interactions require real-time inspection to discover external attacks, malicious actors, and even user errors.
Are you able to provide examples of how global firms are leveraging Securiti’s Data Command Center to interrupt silos and achieve unified data intelligence?
For example, A Fortune 500 company we worked with had complex requirements across data privacy, data security and data governance. We engaged with key members of those teams at the very best levels, including their CPO, CDO and CISO. They complained about having dozens of fragmented tools with the intention to try and procure the information governance they required – and these tools often had inconsistent views of their data. Stitching these systems together to satisfy their obligations on their data was also complex and expensive. They were desirous to harness our solution to get a “single source of truth” about their data landscape that might be utilized by the assorted teams, eliminating inconsistencies and streamlining operations between the groups (e.g., handling cross border transfers or data breaches, which require input from multiple teams). The unified platform improved operational efficiency, reduced complex integration costs and ensured all teams were working from the identical set of information mitigating liability and risks.
Given your extensive background in security, what trends do you see emerging in data security and governance?
Organizations are combating a posh array of products to deal with their data security and governance requirements. One clear trend is the emergence of unified platforms that help reduce costs and complexity and facilitate inter-departmental coordination. One other trend is increased use of AI and automation inside these solutions to assist scale to deal with the explosion of information across hybrid multicloud and the complex array of information regulations. Legacy data discovery and DLP solutions aren’t any longer meeting these needs. Finally, the most important trend of all is the rapid growth in using AI, specifically generative AI. While everyone seems to be accustomed to consumer AI solutions, akin to Chat GPT, the more compelling use case is enterprise AI solutions that may really drive innovation and competitive advantage. To successfully construct enterprise grade AI systems, organizations will need comprehensive controls and data governance solutions to embed appropriate guardrails. Successful organizations might be driving hard to construct progressive AI solutions, which in turn will create the necessity for brand new AI security and governance solutions.
How do you think that organizations should prepare for the challenges and opportunities presented by the increasing use of AI in data management?
The explosion of AI is exciting, but businesses must prioritize responsible implementation to avoid AI becoming a financial or reputational liability. By prioritizing trustworthy AI practices, firms – and their customers – can expect a high level of transparency, control risks, and reputational trust. This implies taking control of your AI landscape, evaluating models for bias and security, continuous monitoring, and ensuring ethical data handling. AI should give you the results you want, not against you.
How does Securiti AI integrate automation in managing data security and privacy, and what benefits does this automation bring to businesses by way of efficiency and compliance?
Securiti AI is built on a foundation of automation, driving efficiency and reducing the danger of human error. By automating tasks like data discovery, classification, and compliance assessments, we unencumber security and privacy teams to give attention to strategic initiatives. Our automation capabilities extend to incident response, threat detection, and remediation – so our customers can react swiftly to security incidents. Moreover, automation plays an important role in ensuring compliance with evolving regulations. By streamlining compliance processes, we help organizations reduce costs, minimize risks, and exhibit their commitment to data protection.
