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Trust, Control, and Safety: The Big GenAI App Challenges
Trust
LLMs are unpredictable & hard to trust
The unpredictable behavior of LLMs can create risks to your reputation and cause compliance issues.
Control
Shipping to production is risky and costly
Unclear LLM performance can lead to delays in launching your product and drive up development costs.
Safety
Challenges to control LLM behaviour & quality
Managing how your model behaves and measuring its quality is tough, requiring specialized knowledge and significant time.
Let's face it. You don't really know if your LLM features are delivering quality results.
1
You're relying on experts to do "vibe checks,” but they are biased and slow.
2
You've tried open source evaluators, but they are too generic for your application.
3
You've embedded basic guardrails, but they're a partial solution at best.
GenAI Apps raise complex questions...
Can you trust your GenAI application?
Trusting your application can be challenging due to unpredictability of LLMs, potential reputational risks, and incompliance with current regulations.
Can you safely ship your App to production?
Shipping your GenAI application to production can cause a lot of delays and increase development costs due to unclarity of LLM performance.
Can you control LLM's behaviour & measure quality?
Evaluating how your models perform, tracking changes, and controlling how it behaves can be a difficult and time consuming task that requires hard data science knowledge.
Get visibility into the “black box” of LLM features — so you can build better products.
“If you aim for medical device classification—you need integrated evaluation tools like Root Signals to confirm that your outputs stay trustworthy and meet those high standards.”
Root Signals makes it easy for tech companies and large enterprises to evaluate and control GenAI-powered applications. SOC 2 Type II certified for enterprise-grade security and compliance.
