Business

Aporia Releases 2024 Benchmark Report, Proves Unmatched Results and Security with Data

Published

2 years ago

August 8, 2024

If results speak volumes, Aporia’s 2024 benchmark report shouts it from the rooftops.

The newly released report showcases their AI Guardrail advancements in artificial intelligence (AI) security and reliability, cementing them as a top AI industry player.

The report comes at a time when the demand for solutions to make AI reliable and secure is at an all-time high, as businesses across various sectors are relying more on AI to drive efficiency. This makes the need for Guardrails more critical than ever. With its low-latency and highly-accurate policies, Aporia’s Guardrails guarantee that AI can be deployed safely.

The Importance of Low Latency and High Accuracy for User Experiences

Businesses, no matter what niche, must always prioritize seamless user experience. This can be achieved through low-latency and high accuracy for AI systems. Whether it is a voice assistant responding to a query or a chatbot handling customer service, the speed and precision of AI interactions can make or break user satisfaction.

Low latency is important for real-time applications, as a slight delay can disrupt the user experience. This is particularly important in sectors like finance and healthcare, where timely and precise information is critical.

High accuracy, on the other hand, helps AI models generate reliable outputs, building on the end-user’s trust. Aporia’s state-of-the-art Guardrails help detect and correct errors with groundbreaking low-latencies and high accuracies, outperforming competitors.

How Aporia Achieves Low Latency

A central factor behind Aporia’s impressive performance is its multi-Small Language Model (SLM) Detection Engine. Unlike traditional approaches that rely on a single large language model (LLM), Aporia’s multiSLM engine uses multiple specialized small language models.

Spreading tasks across multiple models reduces the workload on each model, resulting in faster processing times. This architecture ensures that AI interactions are handled swiftly.

The multiSLM detection engine also enhances the system’s reliability. When one model becomes an issue, the remaining ones can continue functioning and bring uninterrupted service. This redundancy supports the dependability of AI systems, particularly in mission-critical applications.

Aporia Outperforms NeMo, GPT-4o, and GPT-3.5

The report mentions that Aporia’s solutions outperform industry standards like NVIDIA/NeMo, GPT-4o, and GPT-3.5 in latency and accuracy. With an average latency of 0.34 seconds and a 90th percentile latency of 0.43 seconds, Aporia’s solutions are among the fastest in the industry. These figures demonstrate its ability to deliver even in high-demand scenarios.

Aside from low latency, Aporia’s benchmarks reveal superior accuracy in detecting AI hallucinations. The company’s multiSLM Detection Engine outperforms leading models like NeMo and GPT-4o.

While looking at exceptional performance as just numbers may be tempting, it is essential to remember that it translates to real-world benefits for businesses and users alike. After all, Aporia enables companies to deploy AI solutions more confidently, knowing that their systems will respond better.

It is often said that the only constant is change, but in AI, Aporia is proving that top-tier performance can be a constant, too.

Business

Click for Counsel: YesLawyer Wants to Make Lawyers as Accessible as Wi-Fi

Published

6 days ago

April 1, 2026

Matthew Wiles

Photo Courtesy of: YesLawyer

Byline: Andi Stark

For many people facing a legal problem, the most difficult part is not understanding their rights but finding a lawyer willing to speak with them in the first place. Long wait times, unclear pricing, and administrative hurdles often delay even the most basic consultations. YesLawyer, an AI-enabled plaintiff firm operating across all 50 states, is testing whether technology can shorten that gap.

Founded in 2024 by 25-year-old entrepreneur Rob Epstein, the platform offers free intake, automated screening, and, in many cases, same-day conversations with licensed attorneys. The idea is simple: reduce the friction between a client’s first request for help and an actual legal discussion. In this interview, Epstein explains how the system works, where artificial intelligence fits into the process, and what problems the company is trying to address in the broader legal system

Q: When you say you want lawyers to be “as accessible as Wi-Fi,” what does that mean in practical terms?

A: It’s a way of describing speed and availability. Someone dealing with a workplace dispute, a serious injury, or an immigration issue should be able to move from an online form or phone call to a real conversation with counsel in hours, not weeks. YesLawyer is structured so that a client begins with a free case evaluation, goes through automated conflict checks and basic screening, and, in many instances, speaks with a lawyer the same day.

Q: How does the process work once someone contacts the platform?

A: We use a structured workflow. It starts with a short questionnaire and an initial conversation to capture basic facts. That information feeds into conflict checks and internal review. The system then proposes a match with a licensed attorney and provides a calendar link for a virtual consultation, often within 24 hours. After the meeting, the client receives a written legal plan outlining next steps, deadlines, and estimated fees.

Q: Where does artificial intelligence fit into that process, and where does it stop?

A: AI is used for organizing and routing information, not for giving legal advice. It helps with conflict checks at scale, case categorization, and structured summaries so attorneys can focus on the substance of the matter. Every consultation is conducted by a licensed lawyer, and all decisions about strategy or next steps are made by humans.

Q: What problem is this model trying to solve in the current legal system?

A: Delay and cost are still major barriers. Many civil plaintiffs face long waits just to get a first appointment, along with high retainers and hourly billing that make early legal advice risky. We try to respond with faster consultations, flat-fee options, and financing. The idea is to remove administrative friction so lawyers spend less time on logistics and more time speaking with clients.

Q: Some critics say platforms like this blur the line between a technology company and a law firm. How do you describe YesLawyer?

A: We describe ourselves as a national, AI-enabled plaintiff firm that connects clients with independent attorneys. That structure does raise regulatory questions, especially around responsibility and oversight. We focus on licensing verification, attorney-written case plans, and clear communication about fees and services.

Q: You’ve said the main bottleneck is “systems” rather than people. What do you mean by that?

A: The issue isn’t that lawyers don’t want to help more people. It’s that the systems around them make it hard to scale their time. Intake, scheduling, and document handling take hours. Automating those parts means attorneys can handle more matters without being overwhelmed by repetitive tasks.

Q: Does this model risk favoring only the most profitable cases?

A: That’s a real concern in legal technology. Automation often works best for repeatable, high-volume disputes. Our view is that lowering administrative cost can actually make it easier to take on smaller or more complex cases that might otherwise be turned away. Whether that holds over time depends on the data.

Measuring Impact Over Time

YesLawyer’s attempt to compress the timeline between inquiry and consultation reflects broader changes in how legal services are being delivered. As artificial intelligence becomes more common in administrative work, firms are experimenting with new ways to reduce wait times and clarify costs.

The company’s early growth suggests that many clients value faster access to an initial conversation, even before considering long-term representation. Whether this platform-based model becomes widely adopted or remains one of several emerging approaches will depend on regulatory developments, lawyer participation, and measurable outcomes for clients. For now, YesLawyer’s experiment highlights a central question in modern legal practice: how quickly can help realistically be made available to the people who need it.