Agent types in production
Our agent ecosystem divides work into two clean classes: Reasoning Agents that think in real time, and Operational Agents that reliably execute repetitive workflows with speed, safeguards, and predictable cost.
Reasoning Agents
Deep Research Agents
Proactively investigate topics across sources, synthesize findings, resolve contradictions, and propose next steps with citations and confidence measures.
e.g. Investigates key accounts, compares filings and news, and drafts a C-suite briefing with cited risks and opportunities.
Negotiation Agents
Model counterpart interests, propose trade-offs, and draft language that aligns terms, policy guardrails, and acceptable ranges during structured negotiations.
e.g. Suggests alternative indemnity wording to meet policy, offers pricing concessions, and compiles a redlined contract for review.
Knowledge Search Agents
Query knowledge bases and external sources, rank results by relevance and trust, and deliver grounded answers with links.
e.g. Searches product wikis and tickets, explains behavior, and links directly to the canonical troubleshooting runbook steps.
Conversational Agents
Hold stateful dialogues, clarify intent, and orchestrate tools while keeping responses on-brand, compliant, and contextually aware.
e.g. Guides a customer through identity verification, checks order status, and initiates a return with shipping label creation.
Content Generation Agents
Draft long-form or channel-specific content, adapt tone, and embed structured facts while respecting brand and legal guidance.
e.g. Produces a partner announcement, localizes copy, inserts approved claims, and generates alt-text plus meta descriptions.
Data Analysis Agents
Explore datasets, build queries, run statistical tests, and narrate insights with clear caveats, visuals, and decision recommendations.
e.g. Analyzes churn cohort data, fits retention curves, and explains drivers with SQL snippets and chart annotations.
Evaluation Agents
Score outputs against policies, rubrics, or metrics, provide critiques, and recommend targeted fixes to improve quality and safety.
e.g. Reviews marketing claims against legal checklist, flags risky phrases, and proposes compliant rewrites with rationale.
Document Analysis Agents
Parse lengthy documents, extract entities, compare sections, and summarize implications with citations and suggested owner actions.
e.g. Compares MSA versus SOW, highlights conflicting termination terms, and lists remediation options for procurement sign-off.
Coding/Software Engineer Agents
Generate and modify codebases, choose frameworks, write tests, and integrate services while following repository conventions and CI checks.
e.g. Creates a FastAPI service, adds OAuth, writes unit tests, and deploys to staging with database migrations.
Recommendation Agents
Understand product descriptions and help customers with the most accurate product recommendations.
e.g. E-commerce product recommendation agent that brainstorms with a customer and shares recommends the right products.
Operational Agents
Reporting Agents
Compile metrics from trusted sources, format standardized reports, and deliver on cadence with audit trails and distribution lists.
e.g. Aggregates weekly pipeline metrics, reconciles CRM deltas, and emails a board-ready PDF to subscribed stakeholders.
Follow-up Agents
Track outstanding actions and SLAs, send reminders, and log outcomes, escalating respectfully when thresholds are breached.
e.g. Nudges reviewers on overdue PRs, posts summaries in Slack, and escalates to owners after defined grace periods.
Calendar/Scheduling Agents
Coordinate calendars, propose slots, apply preferences, and create invites, rooms, and conferencing with time-zone awareness.
e.g. Schedules a quarterly review across regions, books a conference room, and includes agenda attachments and dial-ins.
Monitoring & Maintenance Agents
Watch services, quotas, and datasets, notify on anomalies, auto-remediate safe issues, and open tickets when necessary.
e.g. Detects failing ETL jobs, retries safely, rolls back partial loads, and files an incident with logs attached.
Data Transformation Agents
Ingest, validate, transform, and enrich data, maintaining lineage and quality checks before updating downstream systems.
e.g. The GenAI equivalent of traditional ETL process designed to handle both structured and unstructured data alike.