The result: Early, targeted validation reduces costly late-stage fixes, accelerates delivery, and increases confidence in safe, effective agentic AI adoption.
SDLC Improvement
Aiceberg’s Role
For AI agent development, validating that the system will behave as intended is critical. Aiceberg’s Listen Mode and Cannon tool simulate real-world usage so autonomous AI addresses the intended business problem and operates within policy before deployment. By analyzing key risk signals—Relevance, Intent, Instruction, and Intent-Instruction Alignment—Aiceberg provides agentic ai governance—ensuring agents follow their design goals, avoid misaligned actions, and deliver expected outcomes.
Keep AI Focused, Accurate, and Aligned
Aiceberg ensures AI-generated content stays contextually relevant and on-task throughout every stage of the software development lifecycle. By filtering out irrelevant or misleading responses, Aiceberg helps teams maintain accuracy, reduce noise, and improve the overall quality of AI-assisted decisions.
This precision isn’t just about efficiency—it’s about security. Irrelevant or off-topic outputs can quietly introduce errors, vulnerabilities, or biased logic into autonomous systems. Aiceberg keeps your AI grounded in context, so every recommendation, line of code, and design decision moves your SDLC forward—safely and intelligently.
Understand What Drives Every AI Interaction
Every enterprise wants to understand why users interact with their AI systems. Aiceberg makes that possible. With over 250 intent classifications, our Guardian Agent reveals what users are truly trying to accomplish, offering visibility into the motivations behind every prompt or command. It’s not just monitoring — it’s understanding behavior at scale.
But insight means little without trust. Aiceberg bridges the gap between human intent and AI action, ensuring every interaction aligns with policy, compliance, and ethical use. You’ll know exactly what your AI is doing — and why — so you can scale confidently without fear of misuse or drift.
Ensure AI Does What You Intend — Nothing More, Nothing Less
Aiceberg validates that AI agents accurately interpret and execute developer intent, ensuring every instruction leads to the right action. By mapping prompts to intended outcomes, it prevents operational drift—keeping AI behavior aligned with business logic, security policies, and compliance frameworks.
From build to deployment, Aiceberg acts as a control layer for autonomous systems, verifying that each action taken by an AI agent matches its authorized purpose. The result: predictable, compliant, and secure performance across your SDLC—so your AI builds with discipline, not risk.
Align Human Purpose with AI Execution [Coming Soon]
Aiceberg bridges the gap between what developers mean and what AI agents do. By harmonizing user intent with instruction generation, it ensures every command is interpreted safely, accurately, and within defined guardrails—no surprises, no missteps.
This alignment forms the foundation of secure, reliable AI development. By preventing misinterpretation and unintended outcomes, Aiceberg safeguards your entire software lifecycle—from planning to deployment—against drift, manipulation, and AI-driven threats. The result is AI that follows intent with precision, protecting both your systems and your reputation.
Get Started with Aiceberg
Send AI interactions to Aiceberg
Route employee AI prompts and responses from SaaS LLMs like ChatGPT into Aiceberg in real-time.
Aiceberg analyzes
The platform detects intent, entity, and detailed code generation review signals.
Forward filtered signals to your SIEM
Only actionable, policy-relevant events are sent to your security tools.
Review Aiceberg dashboard
Access metrics, trends, and insights to guide training, enforce policies, and optimize AI adoption.
