Examples

LEVEL 1: Basic Linear Automation

Trigger → Action(s) → Done

• Automatic Response to Form Submission

  New form submission → Add to CRM → Send confirmation email

• Payment Notifications

  Stripe payment → Create invoice → Notify Slack

• Social Media

  RSS feed → Post to Twitter/LinkedIn

• Email lists

  Spreadsheet or database row → Send templated email

• Personalized EmailsAI

  Generate customized email responses based on recipient data

• Basic FAQ chatbotAI

  Incoming question → Match to knowledge base → Return answer

LEVEL 2: Conditional, Stateful Automation

If/else logic, branching, error handling, basic state tracking

• Lead Scoring System

  High scores are assigned to sales, while lower scores are added to nurture sequence

• Client Onboarding Pipeline

  Send docs, await signature, send reminder if unsigned in 3 days

• Invoice Collection Workflow

  Detect overdue invoices and trigger reminder ladder

• Email ClassifierAI

  Route incoming emails to the appropriate department and escalate based on sentiment

• AI Triage SystemAI

  Analyze support ticket, assign priority and recommend canned response

LEVEL 3: AI-Enhanced Automation

AI used for structured outputs and simple decision making (like which template to use, tone to adopt or follow-up to send). Workflow remains largely deterministic with no long-running reasoning loops.

• Proposal generatorAI

  Pull CRM data, draft a proposal, insert into a template and send for review

• Content repurposing pipelineAI

  Transform a YouTube transcript into summarized social media posts

• Resume screening toolAI

  Extract resume data and score against the job description

• Contract review assistantAI

  Extract risks, flag clauses and generate a summary

LEVEL 4: Agentic Systems

AI agents can reason in steps, call tools, loop until completion and maintain memory.

• Research AgentAI

  • •User asks question
  • •Agent: Searches web, reads documents, summarizes findings, validates sources, returns structured report

• Sales Intelligence AgentAI

  • •User inputs a company name
  • •Agent: Gathers company data, analyzes competitors, identifies ICP match, writes personalized outreach

• Proposal Builder AgentAI

  • •User inputs a discovery call transcript
  • •Agent: Extracts scope, builds pricing, generates contract draft, flags ambiguities

• Internal Knowledge AgentAI

  • •User asks a question
  • •Agent: Searches vector database, retrieves docs, synthesizes answer, asks clarifying questions if needed

LEVEL 5: Multi-Agent Orchestrated Systems

Multi-agent orchestration enables complex, adaptive workflows that can function like a coordinated team of AI workers. While powerful, these systems can introduce significant operational risk and rapidly escalating LLM costs if not carefully designed and constrained. For most of our clients, we prioritize structured AI automation with clear guardrails and measurable ROI over fully autonomous multi-agent systems.

If you're exploring multi-agent systems, we still want to talk to you. In practice, we find that careful architectural design often achieves the same strategic objectives without the complexity and cost profile of a multi-agent build.