A commercial cleaning companyExample
1 · Every business that needs you this month, found.
Each name comes from a sign that the business is about to need you: a move, a hire or a lease running out.
AI agents do the legwork of marketing and sales. Your team wins more deals.
AI agents find the right customers, write to each one, answer every enquiry in minutes, book the meetings, write up every call and keep following up. Your people have the conversations, approve what goes out and get through far more of them.
For businesses of tens to a few hundred people, starting with one day on your own pipeline. AWS funding typically covers the workshop. We’re an AWS Premier Tier partner, one of about 300 among more than 130,000, with 1,300+ engineers.
A river crossing between strangers and customers: AI agents lay the next stepping stone in front of every customer, and your people meet them on the big stones.
Deals are won in conversations.
They’re lost in between.
In a growing business the conversations usually go well enough. What loses the deal is everything between them: the enquiry that waits until morning, the call notes nobody writes up, the quote nobody chases. Nobody decided to drop it. Everyone was busy with the next thing.
- The first reply comes late. When Harvard Business Review audited 2,241 US companies in 2011, 37% answered a web enquiry within an hour.
- Among the companies in that audit that answered within 30 days, the average reply took 42 hours.
- Selling is the smaller part of a seller’s week. In Salesforce’s 2022 survey of 7,775 sales professionals, reps spent 28% of their time selling.
- The rest goes on research, notes, the CRM and chasing, so the follow-up that would have won the deal is the one that slips.
The month beside this is an example.
EnquiriesOctober, an example month
of 40 enquiries lost between conversations, not in one
Example
AI agents do the legwork.
Your people do the talking.
Each AI agent takes one job off your team’s plate, in the CRM, inbox, phone system and calendar you already use. Anything that needs a price, a promise or a judgment call goes to a person. Nine examples, in the order a deal meets them, from nine kinds of business.
A staffing agencyExample
2 · Each one written to, one by one.
Every first message says something true about that business, and where it came from.
A bike shopExample
3 · The right offer to the right customers.
The offer goes to the customers whose orders say they’d buy, and Ana approves the send.
A heating and cooling companyExample
4 · Every enquiry answered in minutes, at any hour.
The customer gets a real answer while they’re still deciding, and anything unusual goes to a person.
An insurance brokerExample
5 · Each enquiry sorted, routed and booked.
It reaches the right person, with the call already in their calendar.
An accounting firmExample
6 · Your person briefed before the call.
The AI agent puts four lines on one card, from the CRM, past emails and the last call.
A software resellerExample
7 · The notes and the CRM written from the call.
The pipeline report is true on Monday, and nobody stayed late to type it.
A marketing agencyExample
8 · The proposal drafted within the hour.
The first draft is priced from your own list, and a person checks and sends it.
A kitchen fitterExample
9 · Every quote followed up, and old ones woken.
The AI agent chases every quote until there’s an answer, and asks the quiet ones again.
Jo, the kitchen fitter’s sales lead, runs themExample
Your people run the AI agents.
Every morning Jo clears the queue: she approves, edits or bins each draft. Her edits teach the AI agents, and a template she has approved unchanged for weeks can go out on its own. Her team spends its days in customers’ kitchens.
An AI agent can write a thousand emails an hour.
That’s the problem.
A small sales team never lacked the means to send more. Sent carelessly, more email means more unsubscribes, a domain on spam lists and customers who stop reading. Winning more deals takes six decisions, each one stopping a failure you’d otherwise meet in front of a customer. Our engineers make them with you, the way Guaranteed AI Outcomes builds every AI system, with AK AI Factory.
One enquiry, tracedA heating and cooling company
from a 9:47 pm web form
to a booked visit
Today: answered the next morning
Example
- 1
Ground: one customer, one record, real sources.
WhyOne email built on a fact the model made up, or a pitch for what they bought last week, and the customer stops reading.
- Every email, call, form and order is matched to one record per customer and company before an AI agent reads anything. Each AI agent sees only the fields its job needs.
- Every fact an AI agent writes about a business, such as a new office, a job post or a renewal date, carries the link or the record it came from, so you can click through the research. No source, no line.
- Prices and terms come from your own price list and policies, so no message quotes a price you don’t charge.
- 2
Orchestrate: plain code wherever it will do.
WhyWithout it come duplicate contacts, two reps calling the same person, and a pipeline nobody believes.
- Fixed steps stay ordinary code: routing by territory, round robin, opening hours, calendar slots and sending limits.
- The model does only the judgment: what an enquiry is asking for, how well it fits, what was said on a call, and the first draft of a reply.
- The CRM stays the record. AI agents write into it, never round it, with a key on every write, so a retry after a timeout writes once.
- 3
Control: nothing new goes out without a person.
WhyNobody hears from you after asking not to be contacted, no customer is offered a discount nobody agreed, and your domain stays off spam lists.
- Code takes card numbers and personal details out of call transcripts before any AI agent reads them.
- Each AI agent has its own identity and a short list of tools, so the one that reads calls can’t send email.
- Drafts wait for a named person: a new message, a discount, a price, a proposal. Most of what an AI agent writes goes out under that person’s own name, and only templates you’ve approved go out on their own, within limits you set.
- Where an AI agent answers on its own, such as a reply to a 9:47 pm enquiry, it says so and offers a person.
- Code checks opt-outs, your do-not-contact list and sending limits before every send, so no AI agent can talk its way past them.
- Mail goes out the way Gmail asks bulk senders to send it: SPF, DKIM and DMARC on your domain, one-click unsubscribe, and spam complaints held under Google’s 0.3% line.
- 4
Prove: tested on last quarter’s real enquiries.
WhyA fit score can look right on a dashboard and still send your team after the wrong customers.
- You and our lead agree one scorecard before we build.
- Your best people label a sample of real enquiries and calls for fit, intent and next step, and we check the AI agent’s labels against theirs, case by case.
- Your team reads the AI agent’s drafts beside its own, unmarked, and answers one question: would you send it?
- A second set stays sealed, so nobody can tune it to pass. If the numbers aren’t there by week 4, we stop.
- 5
Run: in your own account, the cost of a meeting in view.
WhyAn AI bill can grow faster than the pipeline, and someone will ask “why did it send that?”
- It runs in your own AWS account, where recordings, emails and CRM data stay. Models are called through Amazon Bedrock, so the model’s maker never sees your data.
- Every action is traced: which version ran, what it read, what it wrote and what it cost. You can show a customer exactly what was done with their data.
- The cost of each meeting booked sits beside the result on the scorecard, and each job runs on the smallest model that’s as accurate.
- 6
Improve: your team’s edits teach it.
WhyThe same wrong message should never go out twice.
- We keep every edit a person makes to a draft, and the ones that change the meaning become test cases.
- Corrections count too. When someone marks an enquiry “not a fit” or moves a deal an AI agent got wrong, it has to pass that case from then on.
- Replies, meetings and won and lost deals come back as results, so it learns which messages and which customers turn into deals.
- AI agents earn more freedom on evidence, and lose it on a slip.
If I provide a technical requirement, I know it will get done. I’m not seeing any loose ends. That’s a wonderful relief for me knowing that I can trust you guys to get the job done well.
A one-day workshop first.
A go-or-stop in week 4.
- In the morning we map your pipeline as it runs today: from first touch to signed, where enquiries wait, what gets typed twice and which tool holds what.
- In the afternoon we design the target: which steps AI agents take, where your people stay, and what the scorecard measures.
- You leave with a findings report, a target architecture and a costed roadmap, yours to act on with us or without us. AWS funding typically covers the workshop.
- Then comes a go-or-stop decision in week 4, on a scorecard you sign. After that, we’re paid on the result. If the numbers aren’t there, we stop, and you keep what we found.
- The first jobs go live in about 90 days, with a few customers first.
We’ll also tell you what not to do.
- Don’t buy a list and let an AI agent write to all of it.
- Don’t hand an AI agent the conversation that wins the deal. It prepares the conversation, and a person has it.
- If too few enquiries come in at all, AI agents won’t fix that. We’ll say so, and where the money would do more.
ScorecardSigned before we build
Enquiries answered with a real time to meet, within 5 minutes, any hour
Today1 in 5
Target9 in 10
A failure isA message to someone who opted out, or a price that isn’t on your list.
- 0Week
A one-day workshop
- 4Week
Go or stop
- 13Week
Live, a few customers first
Example
We’ve built these jobs before.
Three clients, three of the jobs above. Each started from what the business already had: its calls, its customer records, its CRM.
Ryno Strategic Solutions
Marketing for home services
Under 2 weeks
150+ people analyzed tens of thousands of inbound calls by hand every day. Our AI call analysis now labels each call’s class, disposition and outcome. It was production-ready in under two weeks of a four-week proof of concept, and AWS funded $25,000 of the work.
GORUCK
Outdoor and fitness gear, sold direct
40% higher ROI
Nine platforms held the same customer as up to five records, and campaigns went to broad audiences. With one customer view across all nine, and segments sent automatically to email and ad platforms, targeted campaigns earn 40% higher ROI. Loyalty participation has doubled.
An executive search firm
C-suite and board search
A reasoned shortlist
An AI agent returns a ranked, reasoned shortlist from thousands of candidate profiles, which are enriched from recruiters’ calls and emails and written back to the CRM.
We’re an AWS Premier Tier Services Partner, validated by AWS for agentic AI consulting, with 1,300+ engineers and more than 500 customer launches on AWS. 70% of the proofs of concept we scope reach production.
What owners ask before they start.
Got another? Bring it to the workshop.
We tried an AI sales tool and it spammed people. Why is this different?
Because it’s measured on deals, not on emails sent. The scorecard counts replies, meetings and deals, so sending more never looks like success.
New messages wait for a person until the AI agent has earned more freedom, which means weeks of approvals with almost nothing changed. Every first message says something true about that business, with its source, and the limits in decision 3 are enforced in code.
Our CRM already has AI built in. Why not use that?
Use it where it does the job. The AI built into a CRM works with what’s in that CRM. These AI agents work across your inbox, phone system, calendar, price list and CRM together, each connection one of the short list of tools in decision 3, under your rules and your tests, in your own account, so you keep all of it. Most of what they do lands in the CRM’s own fields, so your team sees nothing new to learn.
Will our sales team push back?
It takes the parts they like least: the research, the notes, the CRM and the chasing. They approve what goes out, their edits teach it, and we build it with them from week 1, so it works the way they sell.
You don’t need a data team or AI engineers. Our engineers build the AI agents with your sales team, inside your business, until they’re live. Then your team runs them, with the runbooks and the record, or we run them for you.
We’re in the middle of contracts with our tools. Do we have to switch?
No. The AI agents work in the CRM, inbox, phone system and calendar you already use. Where a tool has no way in, we say so at the workshop, and sometimes the simplest answer is a small piece of ordinary software instead.
There’s no budget for this quarter.
AWS funding typically covers the workshop, and AWS has funded part of the work for several of our clients. At the workshop we’ll tell you whether yours could qualify.
Nothing goes past week 4 without your go, on numbers you’ve seen. After that, we’re paid on the result.
Bring last month’s enquiries.
Spend one day with the engineers who’d do the work. You leave knowing which steps AI agents should take first, what the scorecard would measure, and whether it’s worth doing at all. AWS funding typically covers the workshop.