The Cost of the Internal Ticket Transfer

Support delays typically stem from an agent waiting for a database to load or a supervisor to reply. This friction costs roughly twenty dollars per incident when factoring in the labor of multiple people touching one ticket. When a customer asks a question that requires a specific lookup, the standard chatbot usually fails. It provides a link to a FAQ or tells the user to wait for a human. This creates the action gap, where teams spend time on tasks that do not represent meaningful work.

Reducing friction between knowing and doing

Resolving a ticket requires more than retrieving a document. An agent often needs to perform a task like checking an order status or updating a shipping address. Duvi agents move beyond retrieval by calling a business's own HTTP APIs or integrating with Salesforce. The agent identifies the user intent and executes the required tool call. This prevents the drain on support resources caused by bots that only talk without acting.

Tool calls happen in the middle of the conversation. If a customer on a live phone call asks to change their billing cycle, the agent uses an API to check eligibility. It then writes the change back to the system of record. No human needs to transcribe the request later. Completed conversations are analyzed into insights so the business can see which tools are used most often. This eliminates the action latency friction where answering a question without updating the database creates a secondary support ticket.

Maintaining context across phone and messaging

Customers often start a query on a website chat widget and want to follow up later via WhatsApp. Most systems treat these as two separate identities, forcing the customer to explain the problem twice. This causes the customer journey to break between the website and messaging apps. Duvi uses the same agent and knowledge base for every surface. The business connects its own phone number or WhatsApp business account through providers like Twilio or Meta.

The logic remains consistent whether the interaction is a live voice call or an asynchronous message. If the agent learns a detail about a customer hardware setup on a phone call, that context exists for the follow up on WhatsApp. A reply always goes back on the channel the customer used. This prevents the data silos that typically occur when a company uses different vendors for their phone system and their chat widget.

Parsing live data instead of static manuals

Documentation changes frequently. A static PDF uploaded to a bot six months ago is likely providing incorrect information about current software versions or pricing tiers. Duvi crawls the business website and parses uploaded files into a vector store. This ensures the agent uses real content to generate its responses. This solves the contact us friction where technical manuals stay hidden from the customer.

When the marketing team updates a service page, the crawler picks up the changes. The agent stops citing the old price and starts citing the new one without any manual retraining. This reduces the risk of hallucinations because the model is constrained to the material it finds on the site or in the provided files.

Launching without an engineering sprint

Deploying an AI agent often requires a months long project involving developers and prompt engineers. Duvi Studio moves this process into a conversation with a builder agent. This builder writes the prompt and selects the model based on the business requirements. Setting up an agent or changing its configuration is free.

The business only pays for usage via credits. This allows a support manager to deploy a specialized agent on a website with a single script tag. If the agent encounters a problem it cannot solve, it hands the conversation over to a human. This structure lets a business bring agents into existing operations without rebuilding their entire technical stack. It also helps businesses avoid phone line bottlenecks that damage marketing ROI.