AGENTS.inc provides autonomous AI agent services for enterprise marketing, sales, and market intelligence, positioned as Agents-as-a-Service rather than chatbots. Its agents fact-check against data from the enterprise's own systems and verify sources before outputs are published, ensuring they are safe to publish and easy to audit. The company is listed by the Everest Group Agentic AI Matrix as one of 27 companies worldwide, alongside Microsoft, Google, Amazon Web Services, IBM, and Salesforce.
Its main capabilities cover six types of tasks:
- Marketing campaign management: the Marketing Agent reads product records, writes copy, builds layouts, and delivers designer-editable files; another agent checks every price before publication.
- Brand monitoring: covers news, regulatory filings, political speeches, patents, and social content, supports all languages in which the enterprise operates, and refreshes continuously.
- Market intelligence: analyzes ten emerging industries in parallel, using a unified format, all sourced from real public materials.
- Lead qualification: conducts first contact via web chat, email, and WhatsApp, completes real qualification conversations, schedules calendar appointments, and writes back to the CRM before the team starts work.
- Customer research: generates research reports, decision-maker identification, written reports, and meeting-ready presentations for target companies.
- Innovation scouting: company discovery, fit analysis, monitoring, contact identification, report and presentation generation, connected end to end.
How it is used and the deployment process: customers provide real business bottlenecks, and AGENTS.inc maps the process, the data involved, and the metrics that should be improved, and provides a specific agent design and cost model. Agents connect to systems of record (such as SAP, Salesforce, DAM, calendars), and trust-layer rules are configured: what counts as a source, what must be cross-checked, and what must not be improvised. Agents work alongside the team, all outputs are reviewed, and grounding rules are adjusted based on real cases until the error rate stabilizes at zero. Agents operate on a base fee plus per-task subscription basis, support unattended operation, and can hand off work to the next agent in the agent cluster.
The company runs on its own infrastructure, and can also be deployed in the customer's own environment according to data residency requirements. The platform provides each agent with an interface suited to its task (not a chat box), including a workspace, task settings, real-time pricing, and token budget; output forms include monitoring dashboards, structured reports, and editable layout docuitems. Every factual claim is deterministically cross-checked against the system of record before leaving the trust layer, with a complete audit trail.
Applicable scenarios include retail FMCG, insurance and finance, energy and utilities, among others. Cases: a major European supermarket generates flyers (copy, structure, layout) directly from product data every week; AXA responds instantly to every inquiry in 94 countries and 50 countries and completes pre-qualification through real conversations; Petrobras and E.ON use it for real-time global reputation monitoring and innovation scouting. Team experience comes from SAP, Volkswagen, Porsche, and Fraunhofer.
Limitations: the materials do not provide specific pricing amounts, a free trial, a complete list of supported languages, API documentation, or a way to access the platform independently. A typical first agent takes four weeks to deploy in a supervised production environment: one week for design, one week for grounding, one week for supervised operation, after which it runs autonomously; complex multi-agent pipelines take longer.
