COMPARISON

Aquant vs. ChatGPT

Capability
Aquant
Purpose-built
ChatGPT logo
ChatGPT
General-purpose
Core Focus
Service-first for complex equipment (OEMs, dealers, service providers).
General-purpose AI for broad knowledge + writing + analysis. Not purpose-built for equipment troubleshooting or service org workflows.
Pre-Built Agents
Dozens of pre-built agents designed for common use cases pre-trained on service language, KPIs, and workflows.  Less time “teaching the platform what service is,” more time fixing customer problems.
No service-specific pre-built agents by default. You can create custom GPTs/assistants, but they typically require you to define the workflow, add content, and engineer prompts/guardrails.
Agent Studio
Anyone can build an agent. Low-code, built for service flows, connects to any CRM and thousands of systems with prebuilt connectors.
Requires connectivity to run reliably (especially for up-to-date answers, tools, and org data access). Not designed as a rugged, field-ready offline troubleshooting experience by default.


Integration
Connects to any CRM and thousands of systems with prebuilt connectors.
Connecting to CRMs/ERPs and executing workflows requires API development, tooling, and governance (and ongoing maintenance). 
Offline Support
Aquant offline is built with the same generative AI capabilities as its online solution. Every second visit is lost margin and lost customer trust. Aquant is built to be used where the work actually happens (often in weak or no connectivity environments).
Requires connectivity to run reliably (especially for up-to-date answers, tools, and org data access). Not designed as a rugged, field-ready offline troubleshooting experience by default.
KPI-Driven Responses
Recommendations tuned to service KPIs e.g. “ FTF and lower MTTR” are defaults, not a long-term customization project.
Can reference KPIs if you prompt it, but KPI prioritization isn’t native. It won’t automatically optimize for FTF/MTTR/parts hit rate/dispatch avoidance unless you consistently instruct it and/or build a KPI logic + feedback layer around it.
Deployment & Ongoing Support
Go live in 4-6 weeks with top use cases.
Typically takes months to set up and then relies on Salesforce admins plus paid consultants or partners to keep agents current.
Cost
$$
Inexpensive and all-inclusive; platform, onboarding, and support bundled. Predictable cost structure as you scale.
$
Inexpensive. Scaling for business use can become seat- and/or usage-based, with additional costs for integrations, governance, data prep, prompt/agent maintenance, and internal ownership.

ChatGPT is powerful, but not built for service

If you build, sell, and service complex equipment, you shouldn’t need long projects, heavy IT dependency, or expensive consulting to get AI working in the real world.

Aquant delivers agentic AI built specifically for service, so value shows up fast, and scales without the usual overhead.
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General intelligence ≠ service intelligence

ChatGPT can answer almost anything, but it doesn’t inherently understand your equipment, failure modes, parts relationships, entitlements, or workflows. Aquant is designed around how OEMs and service organizations operate.

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More work to operationalize at scale

To use ChatGPT reliably across service, you typically need governance, permissions, curated knowledge, and ongoing tuning, plus integration work so it can access the right data. Aquant is purpose-built to deploy in service environments with structure and support.

Signal icon

Not offline-first for the field

Get pre-built agents for common service use cases, plus a low-code builder that plugs into any CRM. And with features like Voice AI and Offline Mode, Aquant is built to work where your techs are at, so they can start seeing value immediately.

Target icon

Not KPI-driven by default

ChatGPT can be prompted to prioritize outcomes, but it won’t naturally optimize for service KPIs like first-time fix or MTTR without customization and validation. Aquant is KPI-driven by design, so recommendations are tuned to measurable service outcomes.

Why Aquant AI is the
Clear Choice

By striking the perfect balance between automation and control, Aquant delivers faster ROI, lower implementation risk, and measurable service outcomes from day one.

Computer chip icon.

Deep Domain Intelligence

A service-specialized Autonomous Linguistics Engine trained on millions of real service tickets, error codes, schematics, and IoT signals.

An Icon of an user getting scanned.

Human-in-the-Loop Automation

Precise insights, action plans, and recommendations that amplify human judgment, never blind autonomy.

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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.

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Reduced Risk & Lock-In

A standalone SaaS platform that integrates seamlessly with any CRM or ERP, no Salesforce licenses required.

The highest trust and security standards

Trust center
security standard logos

FAQ

The agentic AI platform built for your entire service team

Can Aquant's voice AI trigger multiple things at once, like creating a CRM case and handing over to a human expert?

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.

Can Aquant's voice AI authenticate callers so that only pre-authorized individuals can get through?

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!

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Is Aquant multi-modal?

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.

Can Aquant help onboard technicians and get them “field-ready” faster?

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.

Still have questions?

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