Pay As You Go - AI Model Orchestration and Workflows Platform
AI is transforming enterprise productivity, but security remains critical. Companies leveraging AI report 126% more projects completed and 90% higher productivity, yet 78% struggle to integrate AI securely with existing systems. The solution lies in secure, enterprise-grade AI platforms that automate up to 70% of routine tasks while safeguarding data and ensuring compliance.
Prompts.ai offers a secure platform supporting 35+ large language models, real-time cost management, and advanced security features. It enables enterprises to cut AI costs by up to 98% while ensuring compliance and reducing risks like Shadow AI.
Takeaway: Secure AI adoption is essential for scaling productivity and maintaining trust. Platforms like Prompts.ai provide the tools to achieve this balance, empowering teams while protecting critical data.
Enterprise AI Security Statistics and Benefits
Combining strong security measures with operational efficiency, AI platforms provide a reliable foundation for empowering workforces. Below are some of the key features that ensure AI systems are both secure and effective for enterprise use.
Secure AI platforms prioritize data protection through robust encryption methods. This includes AES‑256 encryption for data at rest and TLS 1.2+ for data in transit, along with constant monitoring to identify and address potential security risks.
One standout feature is the non-training clause, which ensures that an organization’s prompts, responses, and proprietary data remain private and are not used to train foundation models. For example, Microsoft emphasizes its multi-layered encryption and rigorous security measures, stating, "Microsoft uses rigorous physical security, background screening, and a multi-layered encryption strategy to protect the confidentiality and integrity of customer content". Similarly, Google Workspace reassures users, "Your data is not reviewed by humans or used for generative AI model training outside your domain without permission".
Data residency controls also allow organizations to dictate where their data is stored and processed, ensuring compliance with local regulations. Advanced platforms often include Enterprise Key Management (EKM), enabling companies to manage their own encryption keys. Additional identity management features - like Multi-Factor Authentication (MFA), SAML-based Single Sign-On (SSO), and SCIM - help ensure that only authorized personnel can access AI tools. For organizations requiring compliance with regulations such as GDPR and HIPAA, providers should offer agreements like a Data Processing Addendum (DPA) and a Business Associate Agreement (BAA).
These measures not only protect sensitive information but also lay the groundwork for effective enterprise governance and detailed audit trails.
To meet compliance requirements and maintain accountability, immutable audit trails are critical. These logs capture key details such as model versions, prompts, responses, and user metadata, helping organizations detect security incidents and ensure adherence to regulations like GDPR, HIPAA, and the EU AI Act. Real-time monitoring further strengthens security by identifying unusual activities, such as prompt injection attacks.
"Immutable audit trails should capture all prompts, responses, and system actions. This provides essential evidence for compliance requirements and security incident response."
Many enterprise platforms have earned compliance certifications, and tools like OpenAI's Enterprise Compliance API allow administrators to access detailed audit logs of conversations and custom GPT interactions.
"Security was at the forefront of our enterprise's most critical needs as we looked to implement a generative AI solution. During our search, we ran a platform 'bake-off' and found that Gemini met all our security needs."
- JK Krug, Vice President of Digital Employee Experience at Equifax
Centralized management tools further empower IT teams to oversee AI adoption, control costs, and ensure these systems are deployed only to approved organizational units. Together, these features enable secure AI implementation while boosting productivity across teams.
Beyond security, smooth integration with existing systems ensures AI platforms enhance workflows without disrupting them. Secure AI platforms are designed to work seamlessly within enterprise environments while maintaining strict security controls. Techniques like Retrieval Augmented Generation (RAG) allow AI systems to retrieve relevant data from internal knowledge bases without permanently storing or integrating that information into the model - ensuring sensitive data remains protected.
Access Control List (ACL) mirroring further safeguards data by ensuring AI tools only display results authorized for specific users. Slack reflects this commitment in its engineering principles, stating, "Customer data is sacrosanct".
Enterprise-grade AI platforms also operate within secure, isolated environments to protect sensitive information. Jeremy Gibbons, Digital and IT CTO at Air Liquide, highlighted this advantage:
"Gemini is in a really unique place in being able to securely access all of our documentation while maintaining the security posture that we have built up over a decade of using Workspace."
- Jeremy Gibbons, Digital and IT CTO at Air Liquide
Frameworks like Google’s Agent2Agent (A2A) Protocol enhance system resilience by enabling AI agents to communicate using structured intents instead of fragile API integrations. Organizations can further strengthen security by adopting a least-privilege approach, granting users access to sensitive data only for the duration of specific tasks. Identity governance tools that automatically revoke access for inactive or orphaned accounts also help minimize risk.
These features ensure that secure AI platforms not only protect sensitive data but also integrate effectively into enterprise systems, enabling teams to work more efficiently and securely.
Prompts.ai takes enterprise security to the next level by combining robust data privacy measures with seamless AI orchestration and cost efficiency. With support for over 35 large language models - including GPT-5, Claude, LLaMA, Gemini, Grok-4, Flux Pro, and Kling - the platform offers a single, secure interface. This unified system removes the need for redundant tools, reduces hidden costs, and simplifies model selection while ensuring centralized management.
Prompts.ai’s platform is designed with an agnostic architecture that integrates smoothly with existing systems. Acting as a centralized control hub, it ensures consistent management across all applications, safeguarding AI operations at every level - from employee tools to custom-built applications and AI code assistants.
"Securing the AI landscape within the enterprise is really challenging. Prompt Security's approach to employees, developers and applications is holistic and encompassing." - Shawn Bower, Chief Information Security Officer at The New York Times
The platform builds on strong security principles, enhancing them with advanced orchestration capabilities. A key feature is the MCP Gateway, which provides real-time, machine-level visibility into AI tasks, ensuring secure management of autonomous agents.
Prompts.ai doesn’t just secure AI - it makes it cost-effective. With transparent token-level tracking and pay-as-you-go TOKN credits, organizations can turn AI expenses into measurable investments, achieving savings of up to 98% on AI tooling.
The platform’s real-time FinOps dashboards give IT leaders instant insights into spending patterns across teams and models. This level of visibility enables businesses to connect AI expenses directly to specific outcomes, transforming AI from a financial uncertainty into a clear, ROI-driven asset.
Prompts.ai is built on deterministic security models and advanced guardrails, ensuring that interactions are limited to their intended use cases while automatically redacting sensitive information. The stateful protection system detects and mitigates multi-turn threats, a critical defense against attackers who spread malicious prompts across extended conversations.
"Prompt Security's comprehensive GenAI Security platform empowers us to innovate at business speed while ensuring we meet industry regulations and protect customer data, giving us the peace of mind we need." - Richard Moore, Security Director at 10x Banking
The platform also features Shadow AI observability, which instantly identifies unauthorized AI tools within the organization. Granular governance controls allow administrators to set detailed policies at both the department and user levels, while comprehensive audit trails provide a clear record of every interaction. For organizations with strict data residency rules, Prompts.ai offers flexible deployment options, including a cloud-based SaaS model or a self-hosted on-premises solution.
Rolling out secure AI software across teams involves more than just technology - it’s a blend of thoughtful planning, effective training, and adaptable workflows. Organizations that approach this as a strategic initiative rather than a simple software installation often experience faster adoption, fewer security issues, and measurable boosts in productivity. The goal is to strike the right balance between speed and safety, ensuring every team member understands both the capabilities and the limitations of AI tools.
The first month is critical for setting a strong foundation. Begin by creating an LLM Registry to catalog all AI endpoints - whether they’re hosted in the cloud, on-premises, or at the edge. Assign clear responsibilities to DevOps leaders, security managers, and executive sponsors to avoid fragmented security and ensure accountability from day one.
Next, draft an AI Governance Charter, a concise document outlining objectives, authority, and budget. This helps build trust across departments while maintaining consistency. Pair this with zero-trust access controls that validate every AI interaction through an internal gateway, checking JWTs, scopes, and device status before access is granted.
Training should emphasize practical safety measures. Teach employees to avoid inputting sensitive personal or company data into AI prompts and to verify AI-generated outputs for accuracy. Implement automated data-handling policies through middleware that sanitizes and masks sensitive information like PII in real time before it reaches the AI model. Conduct governance drills and incident-response exercises - some organizations have reduced breach containment times from hours to just 30 minutes.
| Onboarding Phase | Action | Deliverable |
|---|---|---|
| Discovery | Catalog all LLM endpoints | LLM Registry / CMDB |
| Policy Setup | Define data sanitization and residency rules | Data-Handling Policy |
| Access Control | Assign team-specific API keys (Least-Privilege) | Role-Based Access Matrix |
| Training | Train staff on prompt safety and content review | Training Completion Logs |
| Audit | Forward logs to SIEM (e.g., Splunk, Elastic) | Real-Time Compliance Dashboard |
A comprehensive onboarding process like this sets the stage for scaling AI workflows effectively.
Once onboarding is complete, the next step is to standardize workflows for secure, cross-functional collaboration. 78% of enterprises report that agentic AI has dramatically transformed their operations, with 66% of leaders highlighting measurable productivity gains. The key lies in shifting from disconnected tools to a unified orchestration platform that links systems across IT, HR, and Finance.
Prompts.ai facilitates this transition with multi-agent collaboration, where specialized AI agents - each handling specific tasks like reasoning, perception, or system actions - work together to achieve complex goals. Use session controls to monitor AI application traffic from unmanaged devices, adding stricter restrictions when risks are detected. Apply sensitivity labels to ensure AI-generated content inherits the protections of the original data, safeguarding sensitive information.
To maintain oversight, deploy Data Security Posture Management (DSPM) tools. These tools help identify risky AI usage, oversharing incidents, and gaps in sensitivity labels or DLP policies. For global operations, implement sovereign AI controls to ensure data processing remains within specific regions, such as the US or EU, to comply with local regulations.
After scaling workflows, tailoring AI interactions to specific business needs ensures compliance and enhances value. Generic AI tools often fall short of enterprise requirements. Custom workflows, however, let organizations align AI capabilities with their unique challenges while adhering to regulations. A four-stage lifecycle - identifying risks, measuring their impact, applying technical controls, and maintaining readiness - provides a structured approach.
Incorporate metaprompting to guide AI behavior and set boundaries that reflect organizational expectations. Require human oversight for AI outputs to ensure quality and compliance. Deploy layered content filtering to detect and block malicious activities like prompt injections, jailbreak attempts, or the generation of harmful content.
Use grounding techniques to link prompts to trusted data sources, such as internal files or the public web, to minimize hallucinations. Structure inputs and outputs by limiting their length and employing prompt engineering to enforce specific formats, reducing the risk of undesirable or open-ended responses. For more complex tasks, leverage AI orchestrators to coordinate specialized agents, assigning roles to the most suitable models.
"Gemini doesn't change how we trust Workspace with our data. Gemini doesn't train the model on our data, and features are enterprise-ready as soon as they are released." - Tyler Predale, Director, IT Systems, Flashpoint
Organizations in regulated industries, such as financial services, have achieved zero policy violations over six months by combining automated compliance reporting with strict data residency controls. For retail AI applications, token-budget caps and deterministic output settings have kept operational costs below $2,000 per month. Transparent AI usage, proper citations, and predefined responses for sensitive queries are key to maintaining compliance and building trust.
AI expenses can quickly spiral out of control without proper oversight. Prompts.ai addresses this issue with real-time FinOps AI agents that handle cloud cost diagnostics, detect anomalies, and align budgets - all automatically. Instead of relying on scattered dashboards, stakeholders can simply ask questions like, "Why did my costs increase this month?" and get detailed answers in seconds. These intelligent agents also set autonomous guardrails to monitor spending, eliminating the need for costly per-seat subscriptions. Thanks to pay-as-you-go TOKN credits, organizations only pay for what they actually use, slashing AI software costs by as much as 98% compared to traditional licensing models. This cost efficiency creates opportunities for better team collaboration and smarter resource allocation.
Prompts.ai strengthens collaboration across teams by integrating effortlessly with existing tools and enabling real-time user feedback. Its LLM-agnostic design ensures compatibility with any tech stack, making it easier for teams to adapt and thrive. The results speak for themselves:
"The integration of Prompts.ai's platform has enabled us to provide instant feedback to employees on their use of GenAI, significantly reducing the time and effort required to coach our users." - Sharon Schwartzman, CISO at Upstream
"I found Prompts.ai's approach to reduce the attack surface of LLM applications as powerful, realtime, providing true visibility of the detected threats, while offering practical ways to mitigate it, all with minimal impact to teams' productivity." - Dan Klein, Director of Cyber Security Innovation R&D at Accenture Labs
Prompts.ai goes beyond cost savings and collaboration by strengthening ethical compliance and reducing organizational risks. Shadow AI, where employees use unsanctioned tools, poses a significant threat to enterprise security. Research shows that 35% of employees pay out of pocket for generative AI tools, often bypassing corporate security protocols, with 15% spending $50 or more per month. Prompts.ai provides critical visibility into such unsanctioned tool usage, ensuring controlled and compliant AI adoption.
The platform automatically detects and prevents the exposure of sensitive data, intellectual property, and secrets in prompts or through AI code assistants. It also mitigates risks from toxic or biased outputs generated by LLMs, safeguarding organizational integrity.
"Prompts.ai's comprehensive GenAI Security platform empowers us to innovate at business speed while ensuring we meet industry regulations and protect customer data, giving us the peace of mind we need." - Richard Moore, Security Director at 10x Banking
For organizations like St. Joseph's Healthcare Hamilton, Prompts.ai has been pivotal in their AI adoption strategy. The platform helps them maintain strict data privacy and governance standards, which are critical in medical environments. With 74% of companies reporting a lack of AI expertise among senior leadership, Prompts.ai’s built-in compliance tools and risk assessment scoring make it easier for organizations to establish effective ethical AI governance without requiring advanced technical knowledge.
AI is evolving from simple "copilot" tools to fully autonomous agents capable of managing complex, multi-step workflows. By 2028, it’s expected that 1.3 billion AI agents will be deployed, enabling smoother collaboration across departments. This transformation is reshaping how businesses operate.
However, success in this new era requires more than just advanced AI models. With many companies planning to ramp up their AI investments over the next three years, the challenge lies in balancing innovation with security. Sovereign AI controls now play a critical role, giving organizations the ability to decide where their data is processed, ensuring compliance with regulations. The future will belong to platforms that seamlessly integrate governance into workflows, rather than treating it as an afterthought. This approach empowers leaders to combine cutting-edge AI capabilities with strong oversight and control.
As these trends unfold, IT and innovation leaders must prioritize platforms that combine cost efficiency with rigorous security measures. Security is no longer separate from productivity - they now go hand in hand. Prompts.ai exemplifies this approach by offering unified governance across 35+ LLMs, real-time FinOps capabilities, and flexible pay-as-you-go TOKN credits. This integration of innovation and control has already delivered measurable outcomes, with 78% of enterprises reporting operational improvements from agentic AI and 66% experiencing noticeable productivity gains.
The choice for IT leaders is clear: platforms that provide complete visibility into AI operations, enforce strict access controls, and maintain detailed audit trails are essential. The stakes are high - 80% of business leaders cite data leaks through AI as a major concern, and more than half of successful AI-related attacks through 2029 are predicted to exploit access control weaknesses. Opting for a security-first platform like Prompts.ai is not just about safeguarding data; it’s a strategic move to unlock workforce potential while maintaining trust and confidence in AI-driven operations.
Prompts.ai places a strong emphasis on safeguarding data privacy and security, embedding comprehensive protections throughout its AI workflow platform. Data is encrypted both during storage and while being transmitted, and access is strictly managed via role-based permissions, ensuring that only authorized personnel can interact with sensitive information. Additional features like automatic PII redaction remove personally identifiable information before it reaches AI models, while tamper-evident audit logs securely record all activities for transparency and review.
The platform adheres to stringent compliance standards, including SOC 2 Type II, HIPAA, GDPR, and the AIRTP+ AI-security credential. This makes it well-suited for managing healthcare, financial, and international datasets. Real-time monitoring and comprehensive audit logs further assist organizations in meeting regulatory requirements while quickly addressing any irregularities.
These robust measures enable Prompts.ai to deliver a secure and compliant AI platform, allowing your team to work efficiently without compromising on data protection.
Integrating AI into existing systems comes with its own set of security hurdles. One key challenge lies in protecting the AI models themselves. These models can fall prey to data poisoning, where training data is deliberately manipulated; adversarial attacks, which involve feeding deceptive inputs to mislead the model; and model inversion, a technique used to extract sensitive information from the model. These risks underscore the need to prioritize the protection of both the integrity and confidentiality of AI models.
Data privacy presents another significant concern. AI often depends on large-scale data sharing, which increases the chances of accidental exposure or data leaks, particularly when using third-party or cloud-hosted tools. Handling sensitive information securely and ensuring compliance with privacy regulations is not just advisable - it’s essential.
Additionally, integration points such as APIs, plugins, and orchestration layers can introduce vulnerabilities like unauthorized access or misconfigured systems. To reduce these risks, businesses should embrace secure-by-design practices and establish strong security protocols throughout their AI workflows.
Prompts.ai empowers businesses to cut costs by offering a secure and unified platform that seamlessly integrates more than 35 advanced language models. With built-in encryption and role-based access controls, it minimizes the risk of expensive data breaches while eliminating the need for multiple AI software subscriptions.
By bringing all tools together in one streamlined system, companies can reduce licensing fees, simplify their workflows, and boost operational efficiency - all while upholding top-tier data privacy and security standards.
