Put AI to work in your team's daily tasks.
In many companies AI experiments stay in chat tools that employees use on their own. These tools know nothing about the company’s customers, orders or contracts; the output is copied and moved into another system by hand. Customer service answers the same questions every day and reads incoming emails and documents one by one to enter them.
The AI agents we build work with your company data and your business rules. They understand the question, find the relevant record and do the work in the system; when unsure, or without permission, they hand the task over to an employee together with a summary.
An agent that answers customers
Order status, appointments, returns and frequently asked questions coming in from your website, customer portal or messaging channels are answered around the clock. The agent builds its answer from the customer’s own records and your knowledge base, not from general knowledge. When a conversation moves to an employee it arrives summarized; the customer never has to explain twice.
An assistant beside every rep
Sales and service teams work with an assistant on their own screens: a long case history is summarized in a few lines, a draft reply or quote email is prepared, and before a meeting the customer’s latest status is right in front of them. The rep edits and approves the draft.
From email and document to record
Incoming emails, order forms, invoices and contracts are read; the topic is classified, the required fields are extracted and the right record is created. Instead of entering files by hand, the team only checks the records the agent is not sure about.
Works with your company data
Agents connect to customer, opportunity and case records in Salesforce, order and stock data in the ERP, and the content in your knowledge base. For companies on Salesforce we build with Agentforce; for other setups we use the language models that fit the need.
Safe use
An agent only uses the records the user is allowed to see. Personal data is masked before it reaches the language model, and every conversation and action is logged. Replies to customers about money, contracts or returns go through employee approval, following the rules you set.
Start small, measure, expand
We start with a single task that repeats often and has a measurable result. We test the agent on real conversations and improve it, follow answer quality and handover rate together, and expand to new tasks as results come in.