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Solution

AI Customer Support Automation Across Email, Chat, and Phone

Routine support requests resolved by AI agents that read your systems, complex ones handed to people with the transcript and the record already attached. One assistant across email, chat, WhatsApp, and phone, built on your knowledge and operated after launch.

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Who This Is For

Built for support teams buried in repeat requests

  • Companies whose ticket queue is dominated by order status, account changes, appointment questions, and policy lookups.
  • Teams answering the same questions on email, chat, and phone with inconsistent answers and no shared knowledge base.
  • Businesses that want 24/7 coverage without a night shift or an offshore desk.
  • Operations leaders who need deflection numbers and audit trails, not a chatbot experiment.

What the Solution Includes

From first contact to closed ticket

Triage and routing

Every request classified by intent and urgency, duplicates merged, and cases routed to the right queue with a summary and the customer record attached.

Self-service resolution

Status, changes, cancellations, document requests, and policy questions completed end to end after verifying the customer, with actions logged.

Verified account lookups

Identity checks against your records before any account data is shared, with step-up to a person for sensitive actions.

Omnichannel assistant

The same knowledge and actions on email, website chat, WhatsApp Business API, and phone through our voice stack.

Agent assist

Drafted replies, suggested next steps, and case summaries for human agents on the tickets that still need them.

Reporting

Deflection rate, resolution rate, escalation reasons, response and handle times, and transcript reviews in one dashboard.

The support queue is mostly repeatable

Most tickets ask a question the system can already answer or request a change the system can already make. Agents spend their day on those while the cases that need judgment wait. Automating the repeatable majority does not remove the support team; it gives them back the calls and tickets that deserve a person.

One assistant, every channel

DPI builds the assistant once, on your approved knowledge and your systems, and deploys it to email, website chat, WhatsApp, and phone. Customers get the same answer and the same actions regardless of channel, and agents get the full history when a case reaches them. Identity is verified before account data is shared, and sensitive actions require confirmation or a person.

Operated for quality

Deflection and resolution are only good numbers if the answers were right. We measure accuracy on a test set from your real tickets before launch, review transcripts on a schedule, keep the knowledge base current, and add intents as the numbers justify. Reporting shows deflection, resolution, escalation reasons, and response times monthly.

What you measure

Deflection rate, first-contact resolution, response and handle times, escalation reasons, customer satisfaction where collected, and hours returned to the support team.

How It Works

How a support automation deployment runs

  1. Ticket analysis

    We classify a sample of tickets and conversations by intent, volume, and resolution path, and select the intents worth automating first.

  2. Knowledge and integration design

    Approved knowledge indexed, helpdesk, CRM, and order systems connected, authentication and escalation rules defined.

  3. Pilot on one channel

    The assistant handles selected intents on one channel while agents review outcomes and we tune to the quality bar.

  4. Expand and operate

    More intents and channels added as each proves out, with monthly reviews and reporting.

Stack & Integrations

Support stack and integrations

Helpdesk and ticketing APIs HubSpot, Salesforce, custom CRMs Order, billing, and account systems Website chat, email, WhatsApp Business API Asterisk voice stack over SIP PostgreSQL with pgvector, Qdrant OpenAI, Anthropic Claude, AWS Bedrock, self-hosted models

Industries

Where support automation lands first

Real Estate

Tenant requests, application questions, and status updates.

Engagement Models

Engagement models

Support assessment

Ticket mix, knowledge audit, integration map, projected deflection, and a rollout plan by intent and channel.

Pilot and rollout

Fixed-scope delivery of the first intents on the first channel, then staged expansion.

Managed support automation

Ongoing operation: monitoring, transcript reviews, knowledge updates, new intents, and monthly reporting.

FAQ

Questions about AI support automation

How much of our ticket volume can be automated?

It depends on the mix. Status, changes, and policy questions are highly automatable; complaints and complex cases are routed to people with context. The assessment quantifies achievable deflection from your own tickets before we commit to a number.

Will answers be accurate?

The assistant answers only from approved knowledge and your systems, cites sources where useful, and escalates when unsure. Accuracy is measured on a test set built from real tickets before launch and monitored afterwards.

Does it work with our helpdesk?

We integrate with helpdesk and ticketing systems through their APIs, so automated and human-handled cases live in the same queue with the same reporting.

How do escalations work?

Defined rules send cases to people with the transcript, the customer record, and what was already attempted. Nothing important dead-ends with the AI.

Can it run privately?

Yes. Models can run on AWS Bedrock inside your account or self-hosted, with conversations stored under access controls and retention rules you set.

Related

Next Step

Bring one workflow. Leave with a production plan.

Tell us where calls, tickets, documents, or approvals pile up. We map the workflow, size the impact, and propose a deployment you can measure.

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