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Securiti announced Gencore AI on October 29, 2024, as a platform for building enterprise generative AI systems with company data. Its current product materials describe tools for preparing and governing data, creating permission-aware vector workflows, and applying controls to AI prompts and responses. Those are Securiti’s stated capabilities—not proof that a deployment will be secure or compliant by default.
What is Securiti Gencore AI?
Gencore AI is Securiti’s platform for building enterprise AI copilots and other generative AI projects using organizational data. At launch, the company framed it as a way to connect business data to AI systems while maintaining governance. The current Gencore product page presents a broader set of capabilities spanning data ingestion, preparation, governance, vector database workflows, and runtime controls.
Securiti CEO Rehan Jalil described the launch challenge this way: “For enterprise organizations, the biggest barrier to deploying Gen AI systems at scale is safely connecting to data systems while ensuring proper controls and governance throughout the AI pipeline.” That captures the product’s intended role: helping organizations put controls around the path from source data to AI output.
How Gencore says it handles enterprise data
Ingesting and preparing data
Securiti says Gencore can ingest and vectorize data, extract information from complex files, and prepare datasets by tagging files and removing duplicates or irrelevant content. The product page also describes detecting and redacting sensitive information, with optional dynamic masking according to enterprise policy.
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Gencore’s described DataAI Command Graph is a knowledge graph that connects information about files, columns, sensitive data, entitlements, enterprise controls, AI models, data systems, configurations, and regulations. Securiti says this context can help organizations understand file sensitivity and access entitlements while preparing data for AI use.
The company says it can create permission-aware embeddings for protected vector databases. That capability is relevant to retrieval-augmented generation (RAG), where a system retrieves material from a company’s data stores to inform a response. Buyers should confirm how permissions are enforced at retrieval time, how access changes are reflected, and what happens when a user’s privileges differ from those of the person or process that indexed the source data.
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Supporting different AI workflows
Securiti lists model tuning, training, RAG, enterprise search, and other inference projects as potential uses. These are use cases named by the vendor; the available product materials do not establish that every model, file type, vector store, or deployment pattern is supported.
What runtime protections does Securiti describe?
At runtime, Securiti says Gencore can apply custom or preconfigured policies to prompts and responses. Its listed controls include preventing data leaks, prompt injections, and harmful content, as well as monitoring AI usage through alerts, insights, and violation tracking. The company identifies runtime policy enforcement, RAG data protection, content moderation, and interaction monitoring as typical applications.
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These descriptions should be treated as feature claims rather than guarantees. The product materials reviewed do not provide independent effectiveness testing, quantified customer outcomes, or comparative results. An organization should test its own threat scenarios, including attempts to extract sensitive information, bypass policy, inject malicious instructions through retrieved content, and generate disallowed responses.
What was announced at launch—and what remains unverified?
CSO Online reported Gencore AI’s launch on October 29, 2024, and quoted Jalil saying, “Gencore AI enables organizations to easily and quickly build secure enterprise-grade AI systems.” The same report attributed to him the claim that “Gencore AI automatically protects sensitive information and upholds corporate data governance.” These are executive statements, not independently verified outcomes; organizations remain responsible for evaluating controls against their own policies and compliance obligations.
The 2024 launch coverage also attributed to Securiti descriptions of hundreds of classifiers, more than 400 native connectors, and a graph designed for granular context and billions of nodes. Those are launch-era vendor claims, not independent benchmarks or confirmed specifications for the current product configuration. The report is available from CSO Online.
Integrations, availability, and pricing
Securiti’s Gencore resources hub lists Databricks, NVIDIA, AWS, and HPE in its partners and integrations navigation, and includes materials about using Gencore AI with Amazon Bedrock. This indicates ecosystem associations, but does not by itself establish certification, a specific customer deployment, or the exact integrations available to a particular buyer.
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Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to evaluate Gencore for your organization
Before choosing Gencore or another enterprise AI platform, map its capabilities to your systems, controls, and risk requirements. Ask vendors to demonstrate the relevant workflows with representative data rather than relying only on feature descriptions.
- Data coverage: Which of your data systems and file types can it connect to, and what limitations apply?
- Permissions in retrieval: How are entitlements carried into embeddings and enforced when information is retrieved for different users?
- Data preparation: What cleaning, deduplication, masking, redaction, and lineage features are available, and can your team audit their results?
- Runtime risk controls: Which prompt, response, injection, leakage, and content risks are addressed? How can you test policies and review violations?
- AI stack compatibility: Which models, vector stores, and cloud platforms are supported in the configuration you would buy?
- Operations and deployment: What deployment options, administrative responsibilities, and ongoing operational requirements apply?
- Commercial terms: What features are included, how is pricing structured today, and what contract terms govern usage and support?
Request evidence for security and compliance claims that matter to your environment, and validate controls with your own data, access patterns, and threat models. A platform can support governance work, but buying it does not establish compliance with a law, regulation, or internal policy.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
