The rising concerns over poor privacy guardrails in the world of LLMs and AI created an urgency and demand for a solution. AI privacy tools quickly flooded the market to cater to this demand.
Many enterprises choose LLMGuard, a privacy solution for AI uses cases only to realize that context, accuracy, and auditibility is taking a hit. When security feels like a checklist rather than enabler, its time to explore an alternative.
A word of caution before you choose the best alternative
Before exploring LLMGuard alternatives, it is essential to understand that the “best alternative” is somewhat subjective. If a tool works for a business, it does not guarantee the same for you, and vice versa. The “best” tool ultimately boils down to your specific business use case. We recommend evaluating multiple platforms before making a purchase decision by signing up for a free demo.
LLMGuard alternate #1: Protecto
Protecto AI offers similar but slightly advanced features. Read on to know more about the tool’s capabilities and differentiators.
The platform at a glance: core offerings
Protecto AI is a data privacy and security tool designed specifically for AI and LLM use cases in enterprises. It protects sensitive data by combining AI data guardrails and a privacy vault. Designed to scale horizontally, Protecto maintains context and utility throughout the LLM lifecycle.
PII identification and masking
Protecto utilizes DeepSight, an AI-native sensitive data identification engine designed explicitly for unstructured, high-volume, and context-rich environments, like free text, documents, databases, user logs, and other data stores.
Protecto integrates directly into your data pipeline and is built to handle real-world, high-volume use cases without disrupting workflows. It’s designed to detect PII and PHI in messy, unstructured environments with industry-leading precision.
The platform achieves this through a combination of three advanced AI models, each trained on large, diverse datasets to gain a deep understanding of context, language patterns, and semantics. This multi-model approach dramatically improves accuracy, ensuring sensitive data is correctly identified across edge cases and obscure formats. Once detected, Protecto applies masking, tokenization, or anonymization — depending on your needs and regulatory requirements.
Protecto’s Privacy Vault securely stores original values while exposing only masked or tokenized versions for AI use cases, such as analytics and model training. This ensures AI performance stays strong, without compromising privacy.
Its tokenization engine uses entropy-based methods, making tokens irreversible and secure. Transformer-based NER models boost contextual understanding, while regex patterns, dictionary lookups, and heuristics catch structured identifiers. Together, these techniques create a robust, accurate system for deep data protection, purpose-built for AI.
Product USP (Unique Selling Point)
One of the main differentiators of Protecto is that it is designed to ensure full accuracy of masked data without compromising the output quality. Most tools redact the data which reduces context for AI, whereas Protecto preserves context to eliminate any compromises on the model’s performance.
For example, lets say “John Doe” is tokenized to “A1B2C3” once. Henceforth, wherever “John Doe” is stored or encountered, it will be tokenized to “A1B2C3”. This consistency enables cross-referencing: when AI models see “A1B2C3” in a prompt, it treats it as a name without knowing the actual name. The token can be detokenized for an authorized user at some point later.
Protecto’s advanced AI models detect sensitive data while supporting deterministic rules and regex to ensure full coverage and meet custom needs. This results in better detection rates and minimizes the chances of false negatives.
Lastly, Protecto’s role-based access controls (RBAC), helps to ensure fine-grained governance over who can see original data and who sees masked data. It auto generates audit logs and detailed reports of scans, tokenizations, and unmasking events to help you prove compliance to auditors.
Why should you consider Protecto AI?
Here’s the bottom line: if you’re serious about LLM privacy, Protecto is the tool you want.
- It nails PII and PHI detection with exceptional accuracy across both structured and unstructured data using deep context awareness and smart AI models.
- Its tokenization is context-preserving, meaning you get privacy protection without degrading AI performance. Your models behave like they’re using the original data, but without the risk.
- Protecto delivers a full-stack solution: detection, masking, access control, and compliance reporting all from one unified platform.
- Whether you’re running in the cloud or on-prem, its developer-first APIs plug seamlessly into your ETL workflows, data lakes, or streaming pipelines.
- And if you’re comparing tools, Protecto consistently outperforms Microsoft Presidio and AWS on PII detection; both in accuracy and reliability.
LLMGuard alternate #2: Skyflow
Skyflow has been a prominent player in the data privacy space since 2019. Let’s take a fresh look at what they offer and how they stack up.
Platform Overview
- Skyflow positions itself as a zero-trust privacy vault built to isolate, secure, and govern sensitive data. It stores encrypted or masked data inside its vault and allows access via tokenized APIs. Sensitive data never lives in the open — it’s either locked down or safely exchanged through secure interfaces.
- Key capabilities include deterministic tokenization, granular access controls, policy-driven data governance, and encrypted data operations. The architecture is designed to enforce privacy by default.
Approach to PII Identification and Masking
- Skyflow takes a schema-driven approach to data protection. Rather than relying on AI to scan and classify unstructured text, it uses structured metadata — data schemas and a configurable sensitive data dictionary — to define what qualifies as sensitive. Users manually configure which fields to protect, and the platform routes them to the vault.
- Skyflow does offer some ML-powered context analysis and pattern recognition, but the emphasis is on deterministic policies rather than AI-driven discovery. It favors proactive design over reactive detection — you decide what’s sensitive, and Skyflow ensures it stays protected.
- Encryption is flexible: Skyflow supports polymorphic techniques that adapt based on use case, enabling storage and processing of tokenized or encrypted data depending on operational needs. Sensitive data is excluded or replaced at ingestion, minimizing the risk of it leaking through AI models.
Product Differentiator
- Skyflow’s real edge is its vault-centric, zero-trust architecture. Instead of spreading privacy controls across systems, it consolidates them into a single, hardened layer. Data isolation, governed access, and privacy-preserving computations all happen in one place.
- This makes Skyflow attractive to organizations looking to simplify their stack. It consolidates multiple use cases — payments, PII, LLM protection — into a unified privacy infrastructure, avoiding the overhead of multiple point tools.
Why Choose Skyflow?
- Skyflow offers strong data protection by isolating sensitive fields and managing them through vault-based access. This design drastically reduces the exposure footprint and allows AI models to function without directly handling raw PII or PHI.
- Its policy controls, audit trails, and encryption standards support out-of-the-box compliance with GDPR, HIPAA, and PCI. Teams can safely collaborate on shared data without ever exposing private information.
- Finally, Skyflow is built to plug in easily. It integrates with cloud data warehouses, applications, and databases — allowing privacy to scale with your stack. It’s best suited for teams looking to simplify privacy operations and architect control into their systems from day one.
LLMGuard alternate #3: CalypsoAI
Before jumping to CalypsoAI competitors, let’s take a deep drive into their platform. This will give you an in depth understanding beyond the website copy.
The platform at a glance: core offerings
CalypsoAI is a unified AI security platform that combines red-teaming, real-time defense, and continuous monitoring to secure AI models against a number of privacy risks. Enterprises can protect their AI agents from sensitive data leakage and misuse of data. The system integrates with enterprise tools (SIEM/SOAR) for logging and incident response and scales with low latency to accommodate production workloads.
PII identification and masking
Calypso AI employs a mix of advanced ML/LLM models and rule-based policies. It also uses adversarial attack simulations and reinforcement learning for its red-teaming of models. The architecture is cloud-native but can be deployed to work within an enterprise’s environment.
CalypsoAI’s out of the box scanners combine NER (named entity recognition) and classification models to detect and prevent PII exposure to unauthorized users.
Product USP (Unique Selling Point)
Calypso AI’s key differentiator is its “secure AI inference” focus with GenAI driven
scanners. Organizations can create custom AI security scanners by describing their requirements to translate it into a sophisticated detection policy. This policy-as-code dramatically speeds up developing new guardrails and improves threat adaptability.
Calypso combines pre-deployment testing, in-line defense, and post deployment observability to offer a holistic AI security solution.
Why should you consider CalypsoAI?
CalypsoAI positions themselves as a comprehensive AI security solution that uses preventive and detective guardrails to address a wide range of risks. Some of the pros of the tool are:
- Users can define custom security policies and scanners.
- The system learns and adapts to new and emerging threats.
- Integrates with SIEM/SOAR, supports multimodel and multi-vendor environments
- Maintains low-latency performance at scale
- Provides significant value beyond runtime filtering. The red-teaming tools identifies model vulnerabilities pre-launch
- The observability feature ensures auditability and provides insight into AI behavior
When should you consider an alternative for CalypsoAI?
While CalypsoAI’s robust capabilities help users actively identify and manage AI threats, you should consider another tool if these are important for your use case:
- Steep learning curve and may require coordination between AI developers and security teams. For example, setting up custom policy scanners takes effort and in depth understanding of business context.
- Though Calypso does a solid job in securing text-based LLM applications, it may not suffice if the enterprise needs to protect non textual data like images or data static stores.
- Does not replace a full data anonymization pipeline for training data but complements one by guarding interactions. Users may need to pair it with a solution like Protecto or Skyflow.
Pricing module
Calypso’s does not publicly disclose its pricing; it likely involves custom enterprise licenses or subscriptions. Prospective buyers should expect a significant investment. ROI may be clear for large-scale deployments, but might exceed the budget of smaller organizations.
Still confused? Let us help you
It’s understandable if you still have questions or didn’t get the exact information you wanted.
One way to determine if a tool is right for you is by using the tool for a trial period before making a purchase.
If you are interested in a free trail, or want to discuss your needs, book a demo with our experts.
