Aquant vs. Sierra
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From customer interaction
to service resolution.
The difference isn't whether the platforms can build agents.It's what those agents understand, how they're specialized, and what they can do when the problem involves a physical product.
Built to deliver value fast
General-purpose AI platforms often mean months of implementation, custom work, and consulting before teams see value. Aquant is purpose-built for service, so you can move from idea to impact without a massive program.
Built on real service expertise
General-purpose AI platforms often mean months of implementation, custom work, and consulting before teams see value. Aquant is purpose-built for service, so you can move from idea to impact fast.
Gets smarter over time
Aquant continuously learns from real service conversations, feedback, and outcomes. New failure modes, corrections, workarounds, and customer language feeds back into future interactions, helping the AI continuously improve its understanding of your products.
Service intelligence, wherever work happens
Aquant’s service intelligence lives wherever your customers and teams already work. Deploy, configure, and administer through APIs, embedding Aquant into your CRM, portal, mobile app, connected product, technician workflow, or other application.
Deep Domain Intelligence
A service-specialized Autonomous Linguistics Engine trained on millions of real service tickets, error codes, schematics, and IoT signals.
Human-in-the-Loop Automation
Precise insights, action plans, and recommendations that amplify human judgment, never blind autonomy.
Rapid Time to Value
Pre-built, field-tested agents that get you running in weeks, not months, with no heavy ontology work or custom model training.
Reduced Risk & Lock-In
A standalone SaaS platform that integrates seamlessly with any CRM or ERP, no Salesforce licenses required.
Die höchsten Vertrauens- und Sicherheitsstandards
FAQ
The agentic AI platform built for your entire service team
Absolutely! Roger (Aquant's voice AI) is capable of triggering multiple tasks simultaneously. For example, it can interact with agents built within Aquant’s Agent Studio, third-party agents, or even various third-party MCP tools. It can also connect to a wide range of backend systems through Aquant’s connectivity platform. This means the agent can not only read information from these systems but also modify it as needed. In other words, it’s fully equipped to handle multiple workflows at once, making it really flexible for your needs.
Yes, absolutely! There are a couple of ways to handle authentication. One method is using Roger (Aquant's voice AI) directory of authorized callers, where Roger checks incoming calls against that list and rejects unauthorized ones with a customizable message. Additionally, Roger can also integrate with external identity providers to verify if a caller is authorized. This means it can reach out to these external systems to confirm caller identity before letting them through. All of this is configurable and the caller info can be passed along to downstream CRM tools if you have those set up. This should help ensure only the right callers get through!
Absolutely. Aquant is multimodal in several important ways. Users can interact with it using text, voice, files, and images. Aquant can ingest and reason over complex enterprise content like service manuals, logs, spreadsheets, schematics, tables, images, videos, and even handwritten notes embedded in documents. Outputs are generated by reasoning across all of that content, not just text. And beyond UI-based interaction, Aquant also supports voice AI via phone calls, which adds an entirely new interaction modality for service use cases. So we are multimodal at the input layer, content layer, and interaction layer.
Yes. Aquant can accelerate onboarding with a dedicated Training Agent that supports technicians before and during live jobs. It can:
- Walk new techs through common procedures and troubleshooting flows
- Provide scenario-based practice (symptom → diagnosis → resolution) using real historical cases
- Quiz for understanding and reinforce best practices
- Recommend learning paths based on gaps (e.g., error codes, parts handling, safety steps)
This helps standardize how techs learn and reduces reliance on a small number of senior experts.