We are excited to announce PAIG’s acceptance into Snowflake’s Startup Accelerator program, an highly prestigious program for startups with an extremely high bar. It is a tremendous opportunity to partner closely with Snowflake and bring a world-class solution that provides visibility, security, and governance for AI applications to Snowflake customers through our integration.
We, at PAIG, are dedicated to the security and governance of AI agents in a rapidly and continuously evolving data and IT landscape. As organizations increasingly rely on AI applications, it becomes imperative for Chief Information Officers (CIOs) and Chief Data Officers (CDOs) to gain visibility and enforce AI policies and guardrails. PAIG offers a comprehensive solution to meet these needs, enabling your organization to maximize AI potential while safeguarding data and ensuring regulatory compliance, such as GDPR, HIPAA, and more.
Our mission is to equip organizations with the necessary tools to deploy trustworthy and responsible AI to achieve their goals amid the evolving AI and data landscape. This collaboration with Snowflake reinforces our commitment to enhancing AI application security and governance, allowing you to accelerate your AI initiatives while managing risks and maintaining compliance.
PAIG Understands the Needs of Organizations
As the AI landscape evolves, the importance of security and governance for AI agents cannot be overstated. Organizations must navigate a myriad of risks, including data breaches, compliance violations, and the ethical implications of AI decision-making, while dealing with uncertainty of new threats that didn’t exist in the traditional security and governance world. AI applications are rapidly emerging from a variety of approaches. They range from embedded AI within independent software vendor applications, teams developing AI from the ground up or integrating it with foundational models to organizations implementing their own specialized software that includes AI. Although human governance and oversight are essential to establish necessary structures within organizations, they falter due to the often lack of scalability. This happens due to various reasons, human limitation, lack of automation, lack of pattern detection. Let’s discuss the criticality of this need further.
For instance, three out of every four leaders that we talk to mention the lack of visibility as their top challenge with AI. Governments across the globe have already put together regulations such as the EU AI Act in Europe, Canada’s Directive on AI, and the United States SR-11-7 for the banking industry that require organizations to incorporate robust AI governance and report them regularly. The list goes on. So if you are thinking about AI Governance, then you understand that it goes beyond just compliance and should incorporate several best practices that allow your organization to gain insight and provide continuous monitoring of risks and exposure across their AI landscape with simple-to-understand health and risk metrics. This is where PAIG comes into the picture.
PAIG helps you to address these challenges in alignment with the NIST AI Risk framework (AI RMF), which centers on four core functions of Govern, Map, Measure and Manage. First and foremost, the GOVERN function outlines the necessary organizational structures, processes, and documentation that organizations should establish to anticipate, identify, and manage risks in AI systems.
- Enhanced Visibility (MAP): Enable organizations to inventory and contextualize their AI systems, identifying potential risks and impacts, allowing decision-makers to monitor performance and compliance continuously.
- Evaluate Accuracy & Risks (MEASURE): Provides tools to assess and monitor AI system accuracy, performance, fairness, and security, including metrics for bias, privacy, and reliability.
- Policy Enforcement (MANAGE): Facilitate continuous risk mitigation by automating policy enforcement, incident response, and model monitoring, ensuring that emerging risks are addressed promptly and that AI systems remain trustworthy and compliant.
PAIG’s Solutions for Snowflake Users
For Snowflake users, PAIG offers a robust solution that seamlessly integrates with both Cortex agents and Streamlit applications. This integration empowers users with enhanced control through access checks and safety measures such as content moderation (hate speech, sexual content, misconduct), customizable topics, phrases, and sensitive content including Personally Identifiable Information (PII) detection.
PAIG provides you with a choice based on your needs:
- A fully-managed cloud solution and an open-source server that you can self-host OR
- Available as a native-app on Snowflake.
Unified Oversight with the AI Catalog
Utilizing PAIG, governance teams benefit from a singular interface that consolidates oversight of all AI applications, whether being built in-house with the Cortex platform, or embedded within other platforms like Salesforce or Workday, or in the wild when using applications like OpenAI or other unapproved LLMs and applications. This centralized view facilitates efficient management, enabling teams to monitor and maintain compliance across their AI initiatives.
A Semantic and Metadata Layer for Smarter AI
Paig provides an intelligent semantic and metadata layer designed to boost the accuracy and reliability of Enterprise AI applications within Snowflake and other data platforms. By connecting data to its meaning and context, our system helps AI understand not just the words but the intent behind them. Whether you’re building chatbots, copilots, or search systems, PAIG provides the structured foundation—through knowledge graphs, metadata enrichment, and domain-specific ontologies—that enables your AI to deliver more accurate, relevant, and trustworthy results. No more hallucinations, just context-aware intelligence.
Comprehensive Security and Compliance Framework
PAIG is equipped with out-of-the-box security and compliance policies designed to safeguard AI applications. Depending on your AI journey, your organization can be fine-tuning models using Snowflake, implementing Retrieval-Augmented Generation (RAG) workflows, or leveraging any AI agent framework, including Cortex Agents and PAIG, to ensure consistent security enforcement from the get-go. A crucial component of this framework, PAIG Shield, actively enforces these policies during application runtime.
Advanced Content Moderation
Although LLMs have improved in responding to user questions and avoiding harmful or biased content, they still cannot match each organization’s unique policies and guidelines, making content moderation essential for maintaining compliance and safeguarding organizational integrity. PAIG allows organizations to implement Off-Topic phrases and policies to ensure that the content generated and utilized by AI applications, whether internal or external facing, adheres to established policies. This capability is essential for maintaining compliance and safeguarding organizational integrity.
Customizable Fine-Grained Access Policies
PAIG allows you to construct tailored policies that manage user access to AI applications. By leveraging PAIG Shield, these policies are enforced dynamically, controlling the flow of application access based on user roles and privileges.
Data Filtering & Protection
With Cortex AI, you can use both structured and unstructured data to deliver contextually relevant responses from language models. It is particularly helpful in enforcing data filtering on unstructured data to prevent unauthorized access to private files and documents. PAIG’s capabilities extend to enforcing fine-grained access policies across various data sources, ensuring that only appropriate information is retrieved and presented to users. In addition to content filtering, PAIG also supports data encryption, redacting, and removal of sensitive data for controlled use cases.
Observability, Advanced Auditing & Reporting
PAIG also provides extensive auditing and reporting capabilities. You can access comprehensive audit logs that document user interactions, allowing security and compliance teams to analyze and monitor adherence to established policies. Custom reports and dashboards can be created for ongoing oversight.
Real-World Applications and Use Cases
Snowflake Cortex agents are redesigned to automate complex, multi-step data tasks by orchestrating both structured and unstructured data sources using AI and LLMs. Let us look at some real-world use cases & scenarios and how you can incorporate PAIG with Cortex Agents to solve these.
Claims Agent
A claim officer at a big insurance company can simply use natural language to ask, “Show me all open insurance claims above $10,000 and summarize any related policy clauses.” The agent retrieves claim records from databases and searches policy documents for relevant clauses, providing a consolidated summary without manual intervention.
- The Cortext agent application should first authorize and filter results based on the user’s access & permissions, and also deny access if necessary.
- The Cortex agent is embedded inside the Microsoft Teams app, which is used for user interactions. The user accounts, however, do not exist in Snowflake, which means that the user context should be carried over to Snowflake to appropriately authorize & filter the content based on the user.
- Detects and redacts any PII and sensitive data.
Sales Analytics for Business Users
A sales manager wants to analyze last quarter’s premium customer revenue trends. Traditionally, this would require a developer to write and run a custom SQL query, and the success of text-to-SQL heavily depends on a deeper understanding of the data semantics and ontology within the business domain.
- Using natural language processing (NLP) to understand the user’s intent and identify key entities (e.g., “last quarter,” “premium customer,” “revenue”)
- Mapping these entities to the relevant database schema elements, such as the `sales` table and `revenue` column and further joining them with relevant tables
- Create a well-constructed SQL, execute the query and return the results directly to the Sales manager
PAIG leverages the Snowflake Data Cloud schema to automatically generate a smart semantic and metadata layer. This metadata layer is represented as the enterprise knowledge graph that can be enriched and evolved. This enables automatic mapping and linking of business terms, enriching context and improving the accuracy of the query and the corresponding results.
Take the Next Step Toward Responsible AI
Embarking on this incredible journey alongside Snowflake marks not just another chapter in PAIG’s story. It signifies a giant leap forward for everyone committed to embracing AI with confidence and clarity. We’re thrilled to stand shoulder-to-shoulder with visionaries who share our belief that technology should always serve humanity. As partners in this transformative adventure, we’ll continue to ensure that no matter how fast AI advances, it’s done so responsibly, transparently, and thoughtfully.
If you are interested in a deeper conversation on PAIG and Snowflake partnership, you can schedule your demo here and follow us on Linkedin.
