Emails That Read, Understand, and Act on Themselves
Incoming emails are automatically parsed, classified by intent, enriched with extracted structured data, matched against your knowledge base, and routed to the right agent — or answered directly when the AI has high confidence.
Email Is Where Processes Go to Die
The Unstructured Flood
Emails contain orders, complaints, questions, invoices, and small talk — all in free-form text. Extracting actionable data from this mess is tedious, error-prone, and endless.
Classification by Guesswork
Rules-based routing breaks when customers don't use the right keywords. An email about 'my package hasn't arrived' might be a tracking question, a complaint, or a return request depending on context.
Knowledge Trapped in Threads
Valuable information — customer preferences, product feedback, business relationships — arrives via email and stays buried in inboxes. Nobody extracts and organizes it.
From Email to Structured Action
Email Received
SendGrid inbound parse or Amazon SES/SNS webhook
Parse & Enrich
Extract sender, subject, body, attachments. Load contact profile.
AI Classification
LLM classifies intent: support, order inquiry, complaint, spam
Entity Extraction
Ontology engine extracts order numbers, products, dates, amounts
Knowledge Matching
Extracted entities matched against KB for context
Route or Respond
High confidence → auto-respond. Low → route to specialist or escalate.
Extracted entities stored as queryable knowledge graph nodes
Multi-Provider Inbound
SendGrid inbound parsing and Amazon SES with SNS notifications. Full MIME parsing, HTML-to-text conversion, attachment extraction, and email threading (Message-ID, In-Reply-To, References).
AI Intent Classification
Context-aware classification that goes beyond keywords. The same words mean different things depending on the customer's history, order status, and conversation thread.
Ontology-Based Extraction
Define your domain entities (Order, Product, Customer, Invoice) with typed properties. The AI extracts matching data from every email, building a queryable knowledge graph automatically.
Knowledge Base Retrieval
Embedding-powered semantic search across your knowledge base. Not just keyword matching — the AI understands that 'my delivery is late' is related to your 'Shipping SLA' article.
Confidence-Based Routing
High-confidence responses go out automatically. Ambiguous cases route to specialist agents. True edge cases escalate to humans with full context.
Attachment Processing
PDFs, images, and documents extracted and stored as searchable attachments. Inline images decoded from base64 and saved for clean rendering.
Example: Processing a Forwarded Customer Complaint
Email received via SendGrid
Forwarded complaint with 3 JPEG attachments (damage photos)
Parse & contact lookup
Sender identified, contact profile loaded, conversation thread matched
AI classifies: product_complaint
Intent confidence: 94%. Routes to Product Complaints task.
Ontology extraction
Order #1831966, product BALBRIX500, issue: "damaged on arrival"
Knowledge base match
Return policy for damaged products: full replacement, no return shipping cost
Auto-reply composed
Apology + replacement instructions + internal ticket created for warehouse
Attachments stored
3 damage photos linked to conversation for operations review
95%+
Email classification accuracy with knowledge base grounding
Automatic
Structured data extraction from free-text emails
< 30 seconds
Response time including knowledge base lookup
Results depend on knowledge base coverage and email complexity.
Turn Your Inbox Into an Intelligent System
Deploy AI agents that parse, classify, and act on every incoming email.
