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Forward-deployed for customer experience

Answered sooner, and never trapped with a bot.

Inside Zendesk, Salesforce, or your contact-center platform, we build AI into triage, agent assist, knowledge, and quality review, so customers get a correct answer sooner and agents spend their time on the conversations that need a person.

Request an assessmentHow an engagement runs

Where the hours go

  • Tickets sorted by hand
  • Answers in five places
  • Quality checked by sample
  • Bots that deflect

What a pod builds

  • Triage and routing
  • Agent assist with citations
  • Knowledge drafting and gap detection
  • Self-service that resolves

What gets measured

  • First response time and service level
  • Time to resolution
  • First-contact resolution
  • CSAT and reopen rate

I / Where the hours go

What we look for first.

  • Tickets sorted by hand

    Every ticket is read, tagged, and routed by a person before anyone starts solving it, and misroutes bounce between queues while the customer waits.

  • Answers in five places

    Agents check the help center, Confluence, old tickets, Slack, and a supervisor for the current policy. Two agents can still come back with two answers.

  • Quality checked by sample

    Quality teams score a small sample of conversations each week, so most conversations are never reviewed, and tone, accuracy, and policy problems surface only when a customer escalates.

  • Bots that deflect

    The chatbot handles easy questions, loops on the rest, and passes customers to an agent without context, so they repeat everything to someone starting cold.

II / What we build

Systems, not slideware.

  • Triage and routing

    Reads each incoming email, chat, and voicemail for intent, urgency, language, and sentiment, fills in the ticket fields, and routes it to the right queue. Low-confidence cases go to an agent.

  • Agent assist with citations

    Drafts replies from your current policies and the customer’s order and account history, cites the source for each answer, and writes the after-contact summary. The agent edits and sends; nothing goes out unread.

  • Knowledge drafting and gap detection

    Finds the questions your help center cannot answer by reading resolved tickets, drafts the missing articles in your voice, and flags articles that contradict current policy. Your knowledge owner approves each change.

  • Self-service that resolves

    Answers customers from approved knowledge and their account data, takes the actions you permit (address changes, reorders, and refunds within policy), and hands off to an agent, history attached, whenever the customer asks or confidence drops.

  • Returns, claims, and warranty

    Checks each request against order data, purchase date, photos, and your policy, prepares the return label, replacement, or claim, and holds exceptions and high-value cases for a named approver.

  • QA on every conversation

    Scores every call, chat, and email against your rubric (accuracy, policy, tone, and resolution), and surfaces coaching moments for team leads. Analysts calibrate the scoring, and no score decides an agent’s review alone.

  • Voice of the customer

    Groups tickets, reviews, survey comments, and call reasons into themes with counts and trends, quotes the customers behind each, and sends product and operations a monthly brief of the fixes that would prevent the most contacts.

  • Contact volume forecasting

    Forecasts contact volume by channel, queue, and interval from history, promotions, and known outages, and feeds the forecast to your workforce management tool. Planners still own the schedule.

III / A first vintage

Triage and agent assist

First production deployment, Six to ten weeks

A pod connects triage and agent assist to Zendesk and your knowledge base, runs both in shadow mode on live tickets for two weeks, then hands drafts to the agents on a single queue, who edit and send every reply.

Judged by

First response time, time to resolution, reopen rate, and CSAT on that queue, weighed against what it posted during the Survey.

An illustration of a first deployment, not a description of a past client.

IV / What we measure

Baselined before we build.

  • First response time and service level
  • Time to resolution
  • First-contact resolution
  • CSAT and reopen rate
  • Verified self-service resolution rate
  • Share of conversations quality-reviewed
  • Cost per resolved contact

Set during the Survey and reported every season after.

Systems we work inside

Your stack, not ours.

  • Zendesk
  • Salesforce Service Cloud
  • Intercom
  • Freshdesk
  • Gorgias
  • Kustomer
  • Genesys Cloud
  • NiCE CXone
  • Five9
  • Talkdesk
  • Amazon Connect
  • Twilio Flex
  • Shopify
  • Guru
  • Confluence
  • Notion

Named for familiarity, not partnership. We integrate with what you already run and recommend new tools only when the work requires them.

V / Guardrails

Where people stay in control.

  • Disclosure and handoff

    Each conversation opens by telling the customer they are talking to AI, which the laws of Maine, Utah, and California expect and the EU AI Act has required since August 2026. A person is always one step away.

  • Promises inside policy

    The assistant offers refunds, credits, and exceptions only where written policy allows, and anything beyond it goes to a supervisor. In 2024 a Canadian tribunal held Air Canada liable for a refund its chatbot wrongly promised.

  • Card data kept out

    Card numbers are masked at capture and redacted from transcripts and summaries; PCI DSS forbids keeping security codes after authorization, even in call recordings. Other personal data is redacted to your rules.

  • Cancellation without obstruction

    When a customer asks to cancel, the assistant processes it in the same channel and confirms it in writing. A save offer never blocks the way out, as California’s amended Automatic Renewal Law has required since July 2025.

  • Agent reviews stay with people

    QA scores inform coaching and never decide an agent’s review alone. The EU AI Act classes AI used in performance evaluation as high-risk, with obligations from December 2027, and has banned workplace emotion recognition since February 2025. We design to the first and never build the second.

Related

Work that tends to travel with this.

Begin with the Survey.

Two to three weeks inside your team, a fixed fee agreed up front, and a ranked plan you keep whether or not we build it together.

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