Author: marc

Sherpa by Setfive: A simple way to find the work your team should not be doing

By marc | Leave a Comment on Sherpa by Setfive: A simple way to find the work your team should not be doing

Inside most companies right now, AI is already at work. Even if you have not rolled out ChatGPT Team or Copilot, people are using their personal subscriptions to speed things up. That is great for initiative, not so great for consistency. It looks a lot like the early Excel era: clever workarounds, duplicate effort, and new questions about data governance.

Sherpa is our way to bring order to that energy. We analyze real tasks from Asana or monday.com, group similar work with an LLM, and point to the places where automation will pay off. You get a clear plan you can act on, without buying another stack of licenses first.

What Sherpa is

Think of Sherpa as an AI audit for your task data. It connects to your workspace, reads tasks with your permission, and maps the repetitive patterns that eat time. Then it scores where automation is likely to win, explains why, and recommends how to build it. The output is practical and specific: plays, tools, prompts, and an effort estimate so you can prioritize.

How it works

You start by connecting Asana or monday.com with OAuth. Access is read only and under your control at all times. We do not change or write tasks.

Next, a large language model groups related work and finds recurring patterns. That includes obvious repeats, quiet duplicates that happen across teams, and tasks that often move together in a process.

Finally, we deliver a short report that tells you what to automate, in what order, and how. Each recommendation includes expected time savings, suggested connectors or integrations, and sample prompts so your team can move quickly.

Typical turnaround is about a week from connection to findings.

Why scan tasks now

Personal AI usage is already shaping how work gets done. Sherpa helps you see what is working, what is risky, and what should be standardized. It replaces guesswork with a picture of real workflows, so you can invest in the right automations and avoid paying for licenses that will not get used.

Leaders also get a common view of where hours are going. That makes process conversations easier. Instead of debating tools in the abstract, you can point to specific clusters of tasks and decide how to fix them.

What you get in the report

  • An automation scorecard with high, medium, and low opportunities, each with a short rationale.
  • A top 3 list of automation plays with exact steps, recommended tools, and integration notes.
  • An impact section that translates hours into dollars using your inputs.

You also get a recurring task map, duplicate detection across teams, suggested prompts and connectors, and a next step build plan that you can implement with your team or with Setfive.

A sample finding

Manual reporting shows up in almost every audit. A team exports CSVs every Friday, merges them by hand, and posts a summary. The play is straightforward: schedule the extract, load it to a source of truth, and send a templated summary to Slack or email.

  • Impact: High
  • Effort: Medium
  • Estimated savings: 6 hours per week

If 10 people each save 6 hours per week at an average loaded rate of 75 dollars per hour, that is 6×10×75=4500 dollars of capacity back every week.

Where Sherpa fits with ChatGPT Team and Copilot

Already have licenses? Sherpa shows where to deploy them and turns ad hoc prompts into repeatable, auditable workflows.

Still evaluating? Run Sherpa first to find the highest value use cases, then buy only what you need.

Not ready to buy seats? Many plays use tools you already have, so you can capture savings now and expand later.

Security and privacy

Sherpa uses OAuth with scoped, read only access. You can revoke access at any time. We follow your data retention requirements, and your findings are your IP. We do not use your data to train public models.

Who benefits

Ops and RevOps leaders with checklist heavy processes. PMOs juggling handoffs. CS and Support teams producing weekly reports. Marketing ops moving content through approvals. Finance and People teams closing the loop on routine reconciliations. If the same task shows up again and again, Sherpa will find it.

FAQs

Do we need to change how we work to try it? No. Sherpa analyzes the work you already do.

Will this replace people? The goal is to remove low leverage, repetitive tasks so your team can focus on higher value work.

Can you help implement the plays? Yes. Implementation projects are scoped after the audit.

Try the Free AI Task Audit

Stop guessing where AI will help. Measure it. Sherpa shows you the work your team should not be doing and how to automate it, fast.

Get your Free AI Task Audit, a concise scorecard, and a prioritized plan with savings you can defend.
Ready to see your opportunities? Get in touch at contact@setfive.com or read more about Sherpa at sherpa.setfive.com

Gathering Structured Data From Phone Calls

By marc | Leave a Comment on Gathering Structured Data From Phone Calls

A lot of information these days is just a Google search away, but there is still a surprising number of businesses out there that keep information like pricing locked behind phone lines. Oftentimes, this is deliberate, and they may do this for a variety of reasons:

  • Fluctuating prices that change based on demand, inventory, or seasonality.
  • Sales psychology that converts curious callers into customers.
  • A competitive advantage in keeping pricing opaque to competitors.
  • Personalized quotes that change based on customer need.
  • Old school businesses that just never went digital.

Traditionally, to gather information from these businesses, you would need someone or even multiple people to work through an endless call list, navigating phone menu trees, waiting on hold, and manually transcribing conversations into spreadsheets. This is tedious, expensive, slow, and doesn’t scale.

At Setfive, we decided to look into how we could automate this.

OpenAI Realtime API

The timing couldn’t have been better. As we were exploring ways to do this, OpenAI released its Realtime API, a game-changer for voice-based AI applications. Unlike conventional text-based APIs that require separate speed-to-text and text-to-speech steps, the Realtime API combines these and enables:

  • Low-latency native voice conversations.
  • Natural interruptions for more human-like interactions.
  • Built-in function calling for triggering actions mid-conversation.

This was an AI capable of having an actual over-the-phone conversation.

Building The Bridge

With the brain of the operation sorted, it was time to find a way to actually make phone calls. For this, we chose Twilio, a well-regarded platform for telecommunications for almost two decades.

Twilio’s Media Streams API made it simple to pipe audio directly to and from the OpenAI Realtime API, creating a seamless conversation flow. The business on the other end hears a responsive customer who can handle unexpected conversational turns.

Navigating The Maze

One of the first challenges we ran into? Phone trees. You know them: “Press 1 for appointments, Press 2 to speak to a customer service representative, …” These interactive voice response (IVR) systems are designed for touch-tone input, not voice commands.

We solved this by building AI tools that can simulate DTMF (Dual-Tone Multi-Frequency) signals using Twilio’s API – which required some trial and error with their callback and TwiML architecture – so that our AI can listen to menu options, simulate button presses, navigate complex multi-level menus, and find the fastest path to reach a customer service representative or a front desk.

From Conversations To Structured Data

Getting through to the right person is only half the battle. The real magic happens when our AI finally gets into a conversation. From there, we are able to extract structured information from free-flowing conversations in real time. Using carefully crafted prompts, our system can:

  • Identify key information even when it’s mentioned casually
  • Ask clarifying questions about discrepancies in the information received
  • Extract additional valuable data like availability, pricing details (first-time customer, minimum orders, ect.), and more
  • Create clean, structured data ready for your database, Excel spreadsheet, or whatever else you’re using.

When Nobody Answers

Here’s something we didn’t anticipate: businesses that rely heavily on phone communication are often too busy to answer their phones. These are often small businesses that may not have dedicated staff for handling phones or may have employees who wear multiple hats. They’re not sitting by the phone waiting for calls.

This was having a real effect on our success rate, and we didn’t want to make multiple calls to the same business, hoping for someone to be available. The next step was obvious: voicemail. We enhanced our system to handle a full communication cycle:

  • Intelligent voicemail detection to detect when we have reached a voicemail inbox.
  • Leave a natural message requesting whatever information the AI is looking for.
  • Callback handling that is able to naturally continue the conversation when a business calls back.

Ready to Build?

Interested in how this can help you? Email us at contact@setfive.com to find out more or check out
our demo at voice2data.setfive.com!