In most AI platforms, summaries are generic. They treat a customer support conversation, a sales call, and a job interview the same way—flattening context, missing nuance, and ultimately producing summaries that lack actionable value.
Acta.ai takes a radically different approach.
We've built domain-specific AI agents, each designed to deeply understand the language, structure, and intent behind conversations in a specific business domain. These agents aren't just trained on general NLP—they're optimized for use cases like recruiting, sales, support, internal ops, and more.
How Domain-Specific AI Agents Work
Each agent is:
Context-Aware
Recognizes jargon, processes, and priorities specific to its domain (e.g., recognizing "qualified pipeline" in sales or "cultural fit" in hiring).
Outcome-Oriented
Extracts decisions, assigns action items, and triggers the right next steps.
System-Integrated
Pushes outputs into the tools your team already uses—CRMs, ATSs, helpdesks, calendars, etc.
Role-Tuned
Tailors outputs to different stakeholders. A recruiter, hiring manager, and coordinator all see different, relevant insights from the same conversation.
Examples of Domain-Specific Agents in Action
Recruiting Agent
Understands interviews, scores skills, flags red flags, and updates your ATS.
Sales Agent
Captures objections, next steps, competitor mentions, and sends CRM updates + follow-up drafts.
Support Agent
Flags sentiment, logs resolutions, triggers escalation rules, and creates helpdesk entries.
Meeting Agent
Detects team decisions, assigns responsibilities, and integrates with task/project tools.
The Bottom Line
Domain-specific AI agents are the key to moving from passive documentation to intelligent execution. They give every function in your business its own AI partner—one that doesn't just listen, but truly understands and acts.
Generic AI vs. Domain-Specific AI Agents
| Feature | Generic AI | Acta.ai Domain-Specific Agents |
|---|---|---|
| Understanding of Industry Terms | Limited recognition of specialized terminology | Deep understanding of domain-specific language |
| Workflow Integration | Basic or manual transfer of information | Automatic integration with specialized tools |
| Output Customization | One-size-fits-all approach | Role-specific insights and actions |