AI Agent vs AI Assistant

AI agent vs AI assistant: what's the difference?

An AI assistant responds to your requests. An AI agent plans and acts on its own across steps. Coworker does both, on your real tools, grounded in your company's memory, at frontier quality for about 80% less.

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Connectors

50+

tools it reads and acts across

Lower cost

~80%

vs frontier API rates, via model routing

Security

SOC 2

Type II, GDPR, CASA Tier 2, US-hosted

app.coworker.ai/agents/pipeline-hygiene
Live
Sales Ops

Pipeline Hygiene

routed to Sonnet 4
$0.18

this run

Pulled 247 open opportunities from Salesforce

Salesforce

Flagged 23 stale deals with no activity in 14 days

Salesforce

Drafted nudges for owners in Slack

Slack

Created weekly hygiene report for VP Sales

Notion

agent 1 of 3

Agent vs assistant

One platform that does both

Assistant mode

Conversational help, on demand

Ask a question, request a draft, or get a summary, and Coworker responds in the moment with you in control of each step. This is the assistant pattern: you lead, it helps.

Agent mode

Goal-driven work across steps

Give Coworker an objective and it plans the steps, calls tools, and carries the task forward across your stack. This is the agent pattern: it pursues a goal instead of waiting for each instruction.

Connected to your tools

50+ apps, real actions

Whether it answers or acts, Coworker works across Salesforce, Slack, Jira, Notion, and more, so it operates inside your real systems rather than returning text in isolation.

Organizational memory

Grounded in your company context

OM1 organizational memory maps people, projects, and relationships across your tools, so both assistant answers and agent actions are based on your real context.

Human in the loop

Autonomy with approval gates

Read-only and synthesis steps run automatically, while actions that write or send anything wait for your confirmation. You get agent-level autonomy without losing assistant-level control.

Right model per task

Frontier quality for about 80% less

Intelligent routing sends each request to the best model across OpenAI, Anthropic, Google, and open-source, so assistant and agent work both stay high quality without premium rates on every call.

Built to be enterprise-ready

Security, privacy, and compliance are not add-ons. They're foundational to every layer of the platform.

SOC 2 Type IIVia Secureframe
GDPREU data protection
CASA Tier 2Cloud app security

Permissions & Access Control

  • Role-based access controls (RBAC) with granular permission sets
  • Enterprise SSO via SAML 2.0 and OIDC
  • Multi-factor authentication enforced at every level
  • Scoped API keys with configurable rate limits

Security & Encryption

  • AES-256 encryption at rest, TLS 1.3 in transit
  • Zero-trust network architecture
  • Regular penetration testing by independent firms
  • Vulnerability disclosure and responsible patching

Privacy & Data Governance

  • No training on data
  • Regional data residency – choose where data lives
  • Data retention policies and automated purge controls
  • Full data processing agreements (DPA) available

Scale & Reliability

  • 99.9% uptime SLA backed by enterprise agreements
  • Multi-region, multi-cloud infrastructure
  • Horizontal auto-scaling for peak workloads
  • Disaster recovery with <1hr RPO, <4hr RTO

Controls & Oversight

  • Human-in-the-loop approval gates for sensitive actions
  • Complete audit trails – every agent action logged
  • Real-time monitoring dashboards and alerting
  • Configurable guardrails, rate limits, and kill switches

Deployment Flexibility

  • Cloud, private cloud, or on-premise deployment
  • VPC peering and private endpoints supported
  • Air-gapped environments for regulated industries
  • Bring your own model (BYOM) support
Model Flexibility

Every model. No lock-in.

Coworker works across OpenAI, Anthropic, and Google – as well as secure open-source models. Get ecosystem benefits without ecosystem dependency.

Claude
OpenAI
Gemini
LlamaBeta
MiniMaxBeta
KimiBeta

No ecosystem lock-in

Switch providers freely. Your agents, context, and workflows aren't tied to any single model vendor.

Intelligent cost optimization

Route tasks to the right model for the job. Use powerful models for complex reasoning, efficient open models for routine work.

Secure open-source models

Run open-source models securely and orchestrate workflows across open and closed models.

Dig in:LLM cost calculator·Run Kimi K2.6·OpenRouter alternative·DeepSeek alternative·Qwen alternative

FAQ

Frequently asked questions

An AI assistant responds to your requests: you ask, it answers or drafts, and you stay in control of each step. An AI agent is goal-driven and works more autonomously, planning its own steps, calling tools, and taking action across a task with humans approving key checkpoints. The simplest way to put it: an assistant waits for instructions, an agent pursues an objective.

Neither is strictly better; they fit different jobs. An assistant is ideal for quick, well-defined help where you want to stay in the loop on every step. An agent is better for multi-step work where the path cannot be defined in advance and you want the system to carry a goal forward. Most teams need both, and the best platforms offer both in one place.

Yes. Coworker works as an assistant for conversational, in-the-moment help and as an agent for multi-step workflows that run across your tools. Read-only and synthesis steps happen automatically, while actions like updating a CRM or sending an email route through approval gates, so you get assistant-level control and agent-level autonomy in the same product.

As an assistant: you ask it to summarize a Slack thread and draft a reply, and it returns the summary and draft for you to send. As an agent: you set a goal like triaging new support tickets, and it classifies each ticket, pulls related records, drafts responses, and queues the actions that need a human, working across steps without being prompted each time.

To be useful at work, both need access to your real data and systems. Coworker connects to 50+ tools like Salesforce, Slack, and Jira, grounds answers in your organization's memory, and honors existing permissions, so whether it is acting as an assistant or an agent, it works from your real context and only what each user is allowed to see.

Coworker starts free, with paid plans at $29.99 and $149.99 per month and custom enterprise pricing. Intelligent model routing delivers frontier-quality results for about 80% less than frontier API rates, whether you use it as an assistant or an agent.

Get an assistant and an agent in one

Conversational help when you want it, autonomous workflows when you need them, across 50+ connected tools.