What we automate

Workflows we automate

If the workflow has rules, an agent can run it. Three we run today:

Bookings and reservations, after hours and on overflow

A caller asks for a 10×10 unit at 7:42 PM. The agent checks availability, reserves the unit, sends the payment link, updates the CRM, and texts the confirmation. No hold, no callback.

In production for a self-storage operator on Amazon Connect.

Quotes and proposals

Intake questions feed your pricing rules; the agent drafts the quote, routes anything above your approval threshold to a person, and logs the sent version against the account.

Works from a call, a web form, or an inbound email.

Intake and forms processing

Claims, service requests, and applications captured by voice or web, validated against your rules, created in the system of record, and followed up on a schedule.

A person reviews the exceptions, not the pile.

Also common: appointment confirmations and reschedules, order-status and delivery updates, and account changes that need identity verification first.

What you get

What an engagement includes

One accountable partner from process assessment through go-live and operations.

🔍 Process assessment

Call-driver and process analysis, automation candidates ranked by value and risk, integration readiness, and an ROI model.

🧭 Workflow design

The steps, the decision rules, the exception paths, and exactly where a person signs off.

🔌 Integration

Amazon Connect for voice and chat; your CRM, ERP, property-management or ticketing system through APIs or MCP tools; DynamoDB and EventBridge for state and events.

🧪 Testing

Regression suites built from real transcripts; go-live gated on goal success and tool-call accuracy, not on a demo going well.

🚀 Deployment

One workflow, one channel, live in production in about 60 days, priced against outcomes.

🛠️ Maintenance

Managed AI Operations: monthly performance reviews, prompt regression testing, conversation QA, model and cost optimization, and an AI-spend dashboard.

Human review

Where people stay in the loop

Automation that knows when to stop. Every automated action leaves an audit trail: what the agent heard, what it decided, which tool it called with which values, and what came back.

💵 Approvals above a dollar threshold you set

📜 Anything that changes a contract, policy, or balance

🤝 Ambiguous or upset callers — escalated with full context

⚖️ Regulated disclosures, delivered and logged every time

👀 The first weeks of any new workflow, reviewed daily

Platform

Built on Amazon Connect and AWS

The same stack runs whether the workflow starts with a phone call or a form.

☁️ Amazon Connect

🧠 Amazon Bedrock & Nova

🗣️ Amazon Lex

⚙️ Lambda & DynamoDB

🔁 EventBridge · Twilio where it fits

No contact center required

Many workflows we run never touch a phone line.

If you have a repeatable process with rules and a system of record, it qualifies: appointment confirmations and reschedules, order-status and delivery updates, account changes that need identity verification first, and the back-office half of every call — the CRM update, the follow-up, the record that has to exist afterward.

Scope & pricing

What determines cost, pilot scope, and success

Three things to settle before anyone writes a proposal.

1

Cost

Cost follows three things: how many systems the workflow touches, how many exception paths need designing, and what compliance requires — PHI, recorded-line disclosures, identity verification. Volume matters less than people expect.

2

Pilot scope

One workflow on one channel with a number attached before we start — typically 60 days from kickoff to production, priced against outcomes.

3

Success

Measured on the workflow, not the conversation: completion rate, time to complete, error and rework rate, cost per completed transaction, and customer satisfaction on the automated path.

If those numbers don’t move, the pilot didn’t work — whatever the demo looked like.

Common questions

What happens when the agent gets something wrong?

The design decides that before go-live: thresholds, escalation, and an audit trail, plus regression tests so a fix stays fixed. A wrong value written to a system of record is treated as a defect, not as a bad customer experience — and go-live is gated on tool-call accuracy for exactly that reason.

How long until the first workflow is live?

About 60 days for a production pilot, after a short assessment. We start with the workflow that eats the most time and has the clearest rules, and we put a number on it before kickoff.

Is our data safe?

For healthcare, insurance, utilities, and the public sector, agents and processing pipelines run in secured, governed environments — your data never leaves your control. PHI stays put. Audit trails come standard. And because we cost-engineer the model pipeline, the economics still work at volume.

Bring us the workflow that eats the most time.

Thirty minutes is enough to tell whether it’s a fit and what a pilot would cost.

Discuss Your Workflow →