137 posts on comparisons & alternatives.
CalypsoAI was acquired by F5 in September 2025, which has some teams re-evaluating their inference-layer AI security. This lays out four alternatives, Cisco AI Defense, Lakera, Dynamo AI, and Prompt Security, plus where an identity-bound enforcement layer fits, with honest notes on what each one is built to do.
DeepEval is the pytest-native, open-source standard for scoring LLM outputs in CI, and teams outgrow it in different directions: hosted dashboards, managed red-teaming, or a broader testing scan. This lays out four alternatives, Promptfoo, Giskard, Patronus AI, and Braintrust, plus where a runtime enforcement layer sits, with honest notes on what each one is built to do.
Credo AI is a mature AI governance platform, and teams evaluate alternatives when they want a different framework mix, an observability tie-in, or model-risk depth for a regulated program. This lays out four alternatives, IBM watsonx.governance, Fiddler AI, Arthur AI, and Monitaur, plus where a runtime enforcement layer fits, with honest notes on what each one is built to do.
Dynamo AI came out of MIT research on privacy and federated learning, and its platform now spans DynamoEval for adversarial testing, DynamoEnhance for remediation, and DynamoGuard for real-time guardrails. Teams look at alternatives when they want deeper agent evaluation, an observability tie-in, or identity-bound authorization on live model calls. This lays out three alternatives and where a runtime enforcement layer sits, with honest notes on what each is built to do.
Patronus AI runs automated LLM and agent evaluation, with an open research line (Lynx hallucination detection, Glider evaluator, Percival agent copilot) and a June 2026 Series B aimed at simulated worlds that stress-test agents. Teams look at alternatives when they want eval-as-code, an observability tie-in, or identity-bound authorization on live model calls. This lays out three alternatives and where a runtime enforcement layer sits, with honest notes on what each is built to do.
Robust Intelligence pioneered the AI Firewall and an algorithmic validation engine, now the core of Cisco AI Defense after a reported $400M acquisition. Teams look at alternatives when they want model security without Cisco fabric, or a different control point. This covers CalypsoAI, Lakera, and Protect AI, and where identity-bound runtime enforcement and per-decision audit fit.
AI agent identity has blurred into one marketing message, but the tools underneath do distinct jobs. This buyer guide sorts the field by function: non-human identity security platforms (Astrix, Oasis, Token Security), workload identity brokers and cloud-native IAM (Aembit and the cloud providers), and runtime enforcement plus per-decision audit on the live AI call. Each entry is honest about what it secures and where its boundary sits.
An incident response stack built for endpoints and network traffic has a blind spot when the incident runs through AI traffic, because the prompt content that is the subject of the incident travels inside encrypted API calls that most tools cannot read. This guide walks the five tool categories a 2026 AI incident response stack needs (SIEM, EDR and XDR, SOAR, DLP and CASB, and the AI traffic enforcement and audit layer), what each category does well, and the specific gap each one leaves on AI-agent incidents.
AI audit software is not one product category. It splits into governance and GRC platforms, model evaluation and testing tools, bias and fairness testers, AI traffic audit and enforcement layers, and audit-log integrity tooling. Each proves a different thing, and a team buying "AI audit software" without knowing which category it needs ends up with a policy binder and no request-level evidence. This piece breaks down the five categories, what each one produces for an auditor, and the evaluation criteria that separate real evidence from a dashboard.
On 28 July 2026 Cyera agreed to buy Oasis Security for roughly $1 billion, about $700 million of it cash, weeks after raising $600 million at a $12 billion valuation. It is the second-largest cybersecurity deal of the year and the sixth platform absorption of an AI-agent or identity startup in twelve months. This reads the deal as category validation for identity-bound authorization of AI-agent activity, and sets out the RFP question a platform lead should ask about where that control sits.
WhyLabs was an ML and LLM observability platform built on statistical profiling, maker of whylogs and LangKit. The company wound down its hosted service in early 2025 and open-sourced the platform. DeepInspect is a proxy that decides whether a model call proceeds based on identity and records the decision. This is an honest read on what WhyLabs is now and where runtime enforcement fits.
Vellum is an LLMOps platform for building, evaluating, deploying, and monitoring LLM apps and agent workflows: a prompt playground, evaluation suites, a visual workflow builder, and production monitoring. DeepInspect is a proxy that decides whether a model call proceeds based on identity and records the decision. This walks what each one owns, a feature table, and where a development platform and a security control diverge.