AI for customer communications, across 6 workflow patterns.

Reads incoming customer questions, answers the most common 60-70% of them automatically using grounded responses from the client's knowledge content, and routes anything uncertain to a human with the context already attached. The customer feels supported faster, the support team's queue stays focused on the genuinely hard questions, and answers stay accurate because the pattern grounds every response on real client documentation rather than its training data.

Sits inside the support agent's interface and drafts replies for complex or research-heavy tickets. Reads the incoming ticket, searches past resolved tickets and internal documentation for precedent, and produces a draft response the human agent edits and sends. Never sends autonomously. The pattern accelerates skilled agents on hard cases rather than handling easy cases without them, which is why it shows up in firms where the support workload is complex by nature and full deflection isn't realistic.

A translation layer wrapped around the support workflow. Incoming messages in any supported language are translated for the agent's working interface, the agent replies in their native language, and the outgoing message is translated back to the customer's language before sending. The pattern preserves tone and product-specific terminology by maintaining glossaries the agent or the team can edit. Used by firms with international customers but a single-language support team.

Listens to or processes recorded customer-facing calls, produces accurate transcripts, and generates structured summaries: who said what, what was agreed, what action items emerged, what the sentiment was, and what topics came up. The output flows into the CRM, the support system, or wherever calls are normally documented. Typical use: sales calls, support calls, customer success check-ins. The pattern's job is to make voice conversations searchable and actionable without requiring humans to write notes in real time.

Generates outbound emails that feel personally written but are produced from structured inputs about the recipient and the sender's goal. Common uses: sales outreach to a defined account list, customer success check-ins on a cadence, milestone messages tied to product or contract events. The pattern grounds each email on real facts about the recipient (their role, their company's recent activity, their account state) rather than generating generic copy. Every email is human-reviewable before send, and the pattern is deliberately constrained to one email at a time per recipient — no automated multi-step sequences without human checkpoint.

Watches a shared inbox or distribution alias and classifies each incoming message: what kind of request it is, how urgent, who should own it, what (if anything) the sender wants. Routes the message to the right destination — a person, a team channel, a ticket queue — with a one-paragraph summary so the recipient doesn't have to re-read the original to know what's needed. The pattern's value comes from compressing the human triage step (currently done by someone scanning the inbox several times a day) into something that happens within seconds of arrival.