AI hallucinations: the tendency for AI systems to generate false, misleading, or fabricated responses, have long been the Achilles’ heel of virtual assistants and chatbots. These inaccuracies are not just frustrating; they erode trust, damage customer relationships, and in business contexts, they can cause serious problems.

Neto addresses this challenge directly. With a layered approach rooted in grounding, real-world integrations, and proactive intelligence, Neto’s virtual agents are not just smarter. They are more trustworthy and reliable.

Grounding First: The Multi-Layered Safety Net

Hallucinations happen when AI does not truly understand the accuracy of what it is saying. Neto eliminates this by applying a system of layered large language models (LLMs) that work together to validate every output.

Every Response Is Checked for Sense and Confidence

Before any response reaches your customer, Neto’s virtual agents pass it through a grounding layer that asks: “Does this make sense, and how confident am I in this answer?” This internal check significantly reduces the chance of incorrect or misleading responses.

Context-Aware Filtering

Instead of relying on a single AI brain, Neto uses multiple LLMs, each with a specific role. One generates a potential answer, another verifies its logic, and a third ensures it is based on accurate, up-to-date information. This collaborative system prevents hallucinations before they ever reach your customer.

Action Over Words: Results, Not Guesswork

A major cause of hallucinations is idle conversation. Traditional chatbots often try to "fill in the blanks" when they do not know what to do. Neto flips this model by being action-oriented from the start.

Over 250 Platform Integrations

Neto’s virtual agents do more than talk. They perform real-world tasks like updating customer records, booking appointments, or syncing with your CRM. Each action is based on verified workflows, not assumptions.

Executing Tasks, Not Just Explaining

When customers ask for help, Neto does not merely explain how to complete a task. It takes care of it directly. This focus on action minimizes opportunities for the AI to make things up.

Verified Action Feedback

After completing a task, Neto reports back with real confirmations, not guesses. This creates a trust loop with your customers: ask, execute, confirm.

Ani: The Brain Behind Reliable Conversations

Neto’s intelligent core, Ani, is designed to behave like a true member of your team, with memory, intent, and long-term reasoning.

Proactive Follow-Ups

Unlike traditional chatbots that wait passively, Ani reaches out to users to complete tasks, remind them about open conversations, or check in on progress. This can happen days, weeks, or even months later, ensuring that no task is left unfinished and no detail is invented to move things along..

Memory Across Multiple Conversations

Ani remembers more than just a single session. It builds memory across interactions, helping avoid contradictory responses and ensuring customers are not confused by missing or conflicting details. Accuracy improves over time.

Unified Agent Network: Seamless Collaboration

Many AI agents fail because they operate in silos. Neto’s virtual agents work together like an intelligent network, transferring conversations and context seamlessly.

Smooth Hand-Offs

When one virtual agent cannot complete a task, it does not try to invent a solution. Instead, it hands the conversation off to the right agent within your organization. Neto’s conductor layer ensures that this transfer is seamless and includes the full conversation history.

No Repeating Yourself

Customers never have to restate their issues when they are routed between agents. The entire conversation history moves with them, reducing frustration and eliminating opportunities for error.

Specialized Agents with Shared Knowledge

Neto allows different agents to specialize in areas like sales, support, or billing while sharing the same context. This modular approach keeps responses sharp and grounded, no matter which agent your customer is speaking with.

Deep Data Training Without Guesswork

Traditional AI often struggles to learn from different types of data. Neto’s in-house training LLM is built to consume a wide range of data formats and ground the virtual agent in real business knowledge.

Multimodal Data Processing

Neto’s training systems can handle PDFs, voice notes, videos, livestreams, and phone call transcripts. This rich, multimodal data leads to a deeper, context-aware training process built around your actual business content.

Simple, No-Code Training

You do not need to be an AI expert to train Neto. Upload your documents and content, and the system learns on its own. For more complex setups, Neto’s team is available to help you align your data and goals through strategy calls.

Learning from 1,000s of Conversations

Neto can continuously ingest and learn from your conversation history, allowing your virtual agents to get better over time. Improvements are based on real interactions, not hypothetical scenarios.

Consistency Across Every Channel

Another common cause of hallucinations is the loss of context when switching between communication channels. Neto solves this with full omnichannel support and memory.

Communicate Anywhere

Whether through webchat, email, SMS, or voice, Neto’s virtual agents stay consistent. A customer might text your business at midnight or email during the workday—the agent always remembers the context.

Channel-Independent Memory

Conversations across different channels are combined into a single unified timeline. This prevents misunderstandings and ensures that the AI stays grounded no matter where the conversation happens.

Always Available, Always Consistent

Neto’s agents are online 24/7 and remain consistent in their answers whether a customer contacts them once a day or once a month. This reliability builds trust and reduces the risk of error.

Final Thoughts: Hallucinations Are Not Inevitable

For too long, businesses have accepted AI hallucinations as an unavoidable part of using virtual agents. Neto proves that this does not have to be the case. With Ani at its core, a multi-layered grounding system, and an action-oriented framework, Neto delivers virtual agents that stay accurate, reliable, and grounded in reality.