AI Deployment, Observability & Evaluation

At Sagetap, we are transforming how technology solutions are discovered and evaluated. Our platform is crafted to help tech Vendors connect with leaders in the tech industry, or Sages, effortlessly and efficiently. Our platform exists to facilitate meetings between these tech sellers and tech buyers in a way that ensures buyer anonymity is always protected, preventing any spam or unwanted follow-ups.

Fiddler helps enterprises monitor, conduct root cause analysis, improve, and secure ML, LLM, and GenAI models and applications. * Unified platform for ML, LLM, GenAI, and agentic systems * Custom metrics and dashboards that provide visibility and a holistic view into the performance of how AI systems contribute to organizational KPIs * Fiddler Trust Service which comprises purpose-built, fine tuned models that score LLM prompts and responses at a 6x less expensive rate (compared to LLM as a judge) and are scalable * Fiddler Guardrails that offer <100ms latency and can run in cloud or VPC environments * Available natively in AWS SageMaker * Integrations with NVIDIA NeMO Guardrails and NVIDIA NIM

Tune Security delivers a platform composed of AI-powered capabilities designed for the full range of security stakeholders — including CISOs, SOC managers, and MSSPs. By combining deep cybersecurity expertise with each organization’s specific environment, workflows, and risk posture, Tune enables teams to build, run, and trust AI agents that expand operational capacity, reduce cost, and strengthen defense against modern threats. Tune supports real-world security use cases such as improving SOC visibility and quality assurance, scaling alert triage and investigation, reducing MTTR, and maintaining consistent decision-making across internal and outsourced SOC operations. Tune is designed to be tailored to each organization’s environment, risk posture, and operating model, allowing teams to adopt individual capabilities independently while progressing toward human-led, AI-powered security operations. Tune brings together multiple capabilities under a unified approach to control, safety, and performance, supporting both enterprise SOCs and service providers operating at scale. Customers retain full ownership and control over their data, logic, and permissions, defining exactly how AI agents operate — from human-led assistance to independent execution — all while adhering to deterministic logic, validation checkpoints, and trust-by-design principles, with the level of autonomy fully defined and controlled by the customer. This approach ensures AI capabilities are applied to concrete security outcomes — from improving detection quality and analyst efficiency to enabling reliable, always-on SOC operations — without introducing unmanaged risk or loss of accountability.

Highflame is an enterprise-grade AI security platform built for the age of autonomous agents — providing context-aware guardrails, real-time observability, and unified governance across every AI interaction. Unlike traditional defenses that treat prompts in isolation, Highflame interprets multi-turn context and intent to enforce policies continuously throughout agent workflows, preventing gradual exploit chains, drift, and unsafe actions. At its core, Highflame delivers: • Context-Aware Guardrails: Intent-aware policies that adapt to conversation state and evolving behavior. • Unified Policy Engine: A high-performance policy language with sub-millisecond enforcement across models, agents, tools, and data flows. • Full Interaction Visibility: Live mapping of agents, models, and tools into an Agentic Context Graph for debugging, auditability, and risk insight. • Adaptive Runtime Security: Dynamic enforcement that blocks unsafe content, risky tool calls, data leakage, and malware at the moment it occurs. • MCP Hardening & Tool Protection: Scanning and verifying Model Context Protocol configurations to eliminate downstream risk. • Enterprise-Ready Governance: Continuous audit trails, telemetry, compliance alignment, and dashboards that turn regulation into always-on assurance, not a checkbox. Highflame enables organizations to build, secure, and scale AI systems with confidence, delivering deep visibility, continuous governance, and context-rich defenses across the full lifecycle of agentic workflows.

Highflame Red is an autonomous, continuous AI red-teaming engine designed to stress-test modern LLM applications and agentic workflows at scale. Unlike traditional, point-in-time testing, Red uses swarms of specialized adversarial AI agents that simulate realistic attacker behavior — probing, adapting, and escalating across multi-turn interactions — to uncover vulnerabilities static scans and manual exercises miss. With research-based attack engines, dynamic test generation, and a massive arsenal of curated exploits covering prompt manipulation, data leakage, context drift, model robustness, and unsafe tool use, Highflame Red continuously adapts as your stack evolves. It not only reveals hidden risks but also feeds precise mitigation steps back into runtime guardrails and policy controls to harden defenses automatically. Built for enterprise-grade resilience, Highflame Red delivers: • Autonomous adversarial testing that mirrors real-world threat tactics • Continuous risk discovery across multi-turn, multi-agent scenarios • Guardrail recommendations tailored to your models, tools, and workflows • Resilience scoring & reporting to track posture improvements over time • CI/CD integration for automated testing during development and deployment cycles. By turning red teaming into a continuous learning loop, Highflame Red ensures that defenses evolve alongside AI threats — so teams can find and fix weaknesses before they are exploited.