Juno AI builds workflow automation for brokers and lenders, using domain-specific AI agents that cut processing time, remove manual bottlenecks, and help firms handle more deals without expanding headcount. The company raised a seven-figure round from Fuel Ventures and other fintech investors, adding capital to expand its product and engineering teams. Its platform handles document ingestion, income and risk checks, lead chasing, case progression, and broker-lender coordination in one system. Juno AI also reports strong adoption from brokers and lending firms that want faster case handling and fewer back-office delays. With a focused team, a clear product roadmap, and growing interest from the commercial finance ecosystem, Juno AI is emerging as a company that could reshape how SME and property lending operations run end-to-end.
Founder-led GTM motions often struggle to scale outbound without losing personalization or burning founder time. Identifying vetted accounts, crafting relevant outreach, and managing replies manually isn’t sustainable at scale. Teams need answers: Which accounts show buying signals? Which ones actually convert? Without a system, outbound is guesswork. GTM agents solve this by automating the flow while showing exactly what’s working and why.
Juno AI wanted to build an acquisition system that must have everything in one place – access to 15+ custom account databases, signal-based TAM segmentation, automated enrichment, scoring, and qualification.
They needed fast list creation, 1:1 personalized icebreakers, campaign scheduling, contextual follow-ups, and automated routing of interested leads.
Email infrastructure, deliverability setup, and two-way CRM sync had to be included — no stitching tools together. What made it work wasn’t just the features, but the hands-on support.
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Juno AI was trying to identify financial broker accounts showing strong demand but limited internal sales infrastructure. It looked for UK based teams under 50 headcount, a signal that follow-up, documentation, and CRM hygiene were likely slipping. The absence of sales or ops roles hinted at bandwidth constraints that directly impact deal speed. Senior titles like CEO, Founder, VP, and Director suggested the pain is felt at the top making them more receptive to a fix. Together, these signals highlighted accounts with clear need, high intent, and the right timing for automation.
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Target hot accounts with strong buying signals with both the budget and need for your product.
Act quickly to book meetings within the next 10 days, as these accounts are prime for conversion right now.
Signal 1: Financial Broker Niche – Companies operating specifically in financial broking.
Signal 2: UK Geo Fit – Brokerages headquartered or operating in the UK or USA.
Signal 3: Lean Teams (<50 HC)` – Firms with under 50 employees indicating high ops-automation need.
Signal 4: Exec-Level Targets – CEO/Founder/VP/Director as primary decision-makers.
Now, let’s take a look at how the GTM Agent put this into action.
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The GTM Agent targeted accounts matching the above signals and turned high-intent leads into warm conversations—without any manual follow-ups from the founder. This gave the team bandwidth to focus on closing, while outbound ran on autopilot.
Challenge: The manual, time-intensive process of finding companies actively hiring.
Solution: An AI-powered workflow implemented to automate lead identification, research, and qualification.
Let’s take a look at the flow run by the AI Agent for Juno AI
Juno AI Agent Process and Steps:
The Juno AI Agent process starts with a simple input, much like what a human SDR would begin with. From there, the AI agent searches the public web to identify companies and score & qualify as per signal criterias
Next, it identifies relevant decision-makers (Sr. Execs, Directors) and enriches their profiles with verified email addresses. Once the contacts are ready, the system automatically pushes this enriched data into your CRM or email sequencer (like Smartlead), setting the stage for targeted outbound campaigns.
This end-to-end automation helps SDR teams skip hours of manual research and focus only on high-probability conversations.
.png)
Human-in-the-Loop Campaign Management. While GTM Agents are autonomous, every campaign benefits from an expert-led human-in-the-loop (HITL) architecture that ensures precision, adaptability, and reliability—especially in complex SaaS and GTM environments where AI alone may fall short.
The campaign engine is supported by real humans with deep expertise in GTM systems, making the service resilient, customizable, and highly contextual.
What This Means for the Juno AI Team:
● No DIY configurations — Our team handles all technical setup, infrastructure, and sequencing logic.
● No risk of failure — If the AI agent cannot process a domain, extract signals, or validate contacts, our human experts step in immediately.
In this sprint we could identify 50+ accounts that are in fits show signal level hot and fits ICP fit.
.png)
GTM Agent handled large daily send volumes with zero drop in performance. Maintaining a steady 1.5% reply rate across the entire outreach window.
.png)
This section uses a container element to ensure the content looks right on every device. It’s centered with the class “Centered Container.”
Convert!If you're targeting customer service managers, than you'll need a pitch that completely resonates with them.
But how do you write emails that strike are a perfect balance between promoting your business but not being too self-centered?
In this article, Sacha, CEO of Growth Room, shows how social proof helps you transform a cold email into a powerful tool that books meetings!
Here's an example of a cold email that targets customer service (CS) managers in e-commerce to sell an AI-powered CS platform 👇
Here are Sacha’s insights on what needs to be improved to get more replies:
Mistake #1 → Too promotional subject line
Avoid using popular marketing and sales keywords such as “boost”, “customer service”, and “AI” which won’t make your cold email stand out in prospects’ inboxes.
Mistake #2 → Self-centered intro line
The intro line should catch prospects’ attention by talking about them and what you can do for them. Talking about yourself won’t bring them value and interest them in reading the rest of your email.
Mistake #3 → Not-visible CTA
Because your prospects usually scan emails before reading them, adding a space line before the ending line will make their next step more clear.
Mistake #4 → Spam words
If you want to ensure your messaging gets through, avoid using spam words like “free”. Those words trigger the spam filters and land your emails in the spam folder where your target audience can’t read them.
Here is how Sacha would rewrite the previous cold email and his tips for booking more meetings!
Tip #1 → Focus on your prospect
If you want to get replies to your cold emails - talk about their company, compliment them, and ensure the majority of your email is focused on them and how to achieve their goals.
Tip #2 → Give a glimpse of the value you bring
By leveraging social proof, you can showcase prospects’ desired outcomes and tease them into replying. Mention clients and their results from relevant industries to build trust and credibility.
Tip #3 → Position yourself as an expert
Position yourself as a problem solver. Once you show your leads that you understand their pain point and know how to solve it, it will make your product/service more relevant.
Tip #4 → Non-intrusive CTA
Instead of talking about demos, ask for less effort and talk about catching up over a call/meeting. It will sound less salesy and push your prospects to reply.
Here are Sacha’s tips for effective cold emailing to sell AI-powered platforms to e-commerce CS managers:
-> Focus on the recipient, highlighting their company and goals
-> Utilize social proof relevant to their industry to establish trust
-> Position yourself as a solution to their specific challenges
-> Use a non-intrusive call-to-action, like suggesting a casual call or meeting instead of demo
Cold emails work effectively when they are targeted, personalized, clear, and part of a well-thought sales strategy.
Here are 5 best practices that will make your cold outreach effective and help you get results:
Cold emails can be effective when they are highly targeted. This means understanding the recipient's industry, role, and potential needs, and then crafting an email that speaks directly to those factors.
A key element of successful cold emails is personalization. This goes beyond just using the recipient's name; it involves tailoring the message to address their specific challenges or interests.
The effectiveness of a cold email is often tied to its clarity. As the majority of recipients first scan cold emails, they are more likely to engage with the ones that get to the point quickly and offer a clear value proposition.
Persistence in cold outreach pays off! Follow-up emails, when done respectfully and increasing the value, can boost the chances of getting a reply.
The success of cold emails should be measured not just by open or response rates, but also by the quality of the interactions they initiate (e.g., established connections, closed deals)
Salesloft can be used in Large Enterprises, Mid Size Business, Non Profit, Public Administrations, and Small Businesses.
It was built for the entire revenue teams to optimize customer journey:
Juno AI builds workflow automation for brokers and lenders, using domain-specific AI agents that cut processing time, remove manual bottlenecks, and help firms handle more deals without expanding headcount. The company raised a seven-figure round from Fuel Ventures and other fintech investors, adding capital to expand its product and engineering teams. Its platform handles document ingestion, income and risk checks, lead chasing, case progression, and broker-lender coordination in one system. Juno AI also reports strong adoption from brokers and lending firms that want faster case handling and fewer back-office delays. With a focused team, a clear product roadmap, and growing interest from the commercial finance ecosystem, Juno AI is emerging as a company that could reshape how SME and property lending operations run end-to-end.
Founder-led GTM motions often struggle to scale outbound without losing personalization or burning founder time. Identifying vetted accounts, crafting relevant outreach, and managing replies manually isn’t sustainable at scale. Teams need answers: Which accounts show buying signals? Which ones actually convert? Without a system, outbound is guesswork. GTM agents solve this by automating the flow while showing exactly what’s working and why.
Juno AI wanted to build an acquisition system that must have everything in one place – access to 15+ custom account databases, signal-based TAM segmentation, automated enrichment, scoring, and qualification.
They needed fast list creation, 1:1 personalized icebreakers, campaign scheduling, contextual follow-ups, and automated routing of interested leads.
Email infrastructure, deliverability setup, and two-way CRM sync had to be included — no stitching tools together. What made it work wasn’t just the features, but the hands-on support.
Juno AI was trying to identify financial broker accounts showing strong demand but limited internal sales infrastructure. It looked for UK based teams under 50 headcount, a signal that follow-up, documentation, and CRM hygiene were likely slipping. The absence of sales or ops roles hinted at bandwidth constraints that directly impact deal speed. Senior titles like CEO, Founder, VP, and Director suggested the pain is felt at the top making them more receptive to a fix. Together, these signals highlighted accounts with clear need, high intent, and the right timing for automation.
Target hot accounts with strong buying signals with both the budget and need for your product.
Act quickly to book meetings within the next 10 days, as these accounts are prime for conversion right now.
Signal 1: Financial Broker Niche – Companies operating specifically in financial broking.
Signal 2: UK Geo Fit – Brokerages headquartered or operating in the UK or USA.
Signal 3: Lean Teams (<50 HC)` – Firms with under 50 employees indicating high ops-automation need.
Signal 4: Exec-Level Targets – CEO/Founder/VP/Director as primary decision-makers.
Now, let’s take a look at how the GTM Agent put this into action.
The GTM Agent targeted accounts matching the above signals and turned high-intent leads into warm conversations—without any manual follow-ups from the founder. This gave the team bandwidth to focus on closing, while outbound ran on autopilot.
Challenge: The manual, time-intensive process of finding companies actively hiring.
Solution: An AI-powered workflow implemented to automate lead identification, research, and qualification.
Let’s take a look at the flow run by the AI Agent for Juno AI
Juno AI Agent Process and Steps:
The Juno AI Agent process starts with a simple input, much like what a human SDR would begin with. From there, the AI agent searches the public web to identify companies and score & qualify as per signal criterias
Next, it identifies relevant decision-makers (Sr. Execs, Directors) and enriches their profiles with verified email addresses. Once the contacts are ready, the system automatically pushes this enriched data into your CRM or email sequencer (like Smartlead), setting the stage for targeted outbound campaigns.
This end-to-end automation helps SDR teams skip hours of manual research and focus only on high-probability conversations.
Human-in-the-Loop Campaign Management. While GTM Agents are autonomous, every campaign benefits from an expert-led human-in-the-loop (HITL) architecture that ensures precision, adaptability, and reliability—especially in complex SaaS and GTM environments where AI alone may fall short.
The campaign engine is supported by real humans with deep expertise in GTM systems, making the service resilient, customizable, and highly contextual.
What This Means for the Juno AI Team:
● No DIY configurations — Our team handles all technical setup, infrastructure, and sequencing logic.
● No risk of failure — If the AI agent cannot process a domain, extract signals, or validate contacts, our human experts step in immediately.
In this sprint we could identify 50+ accounts that are in fits show signal level hot and fits ICP fit.
GTM Agent handled large daily send volumes with zero drop in performance. Maintaining a steady 1.5% reply rate across the entire outreach window.
This section uses a container element to ensure the content looks right on every device. It’s centered with the class “Centered Container.”
Convert!Juno AI builds workflow automation for brokers and lenders, using domain-specific AI agents that cut processing time, remove manual bottlenecks, and help firms handle more deals without expanding headcount. The company raised a seven-figure round from Fuel Ventures and other fintech investors, adding capital to expand its product and engineering teams. Its platform handles document ingestion, income and risk checks, lead chasing, case progression, and broker-lender coordination in one system. Juno AI also reports strong adoption from brokers and lending firms that want faster case handling and fewer back-office delays. With a focused team, a clear product roadmap, and growing interest from the commercial finance ecosystem, Juno AI is emerging as a company that could reshape how SME and property lending operations run end-to-end.
Founder-led GTM motions often struggle to scale outbound without losing personalization or burning founder time. Identifying vetted accounts, crafting relevant outreach, and managing replies manually isn’t sustainable at scale. Teams need answers: Which accounts show buying signals? Which ones actually convert? Without a system, outbound is guesswork. GTM agents solve this by automating the flow while showing exactly what’s working and why.
Juno AI wanted to build an acquisition system that must have everything in one place – access to 15+ custom account databases, signal-based TAM segmentation, automated enrichment, scoring, and qualification.
They needed fast list creation, 1:1 personalized icebreakers, campaign scheduling, contextual follow-ups, and automated routing of interested leads.
Email infrastructure, deliverability setup, and two-way CRM sync had to be included — no stitching tools together. What made it work wasn’t just the features, but the hands-on support.
Juno AI was trying to identify financial broker accounts showing strong demand but limited internal sales infrastructure. It looked for UK based teams under 50 headcount, a signal that follow-up, documentation, and CRM hygiene were likely slipping. The absence of sales or ops roles hinted at bandwidth constraints that directly impact deal speed. Senior titles like CEO, Founder, VP, and Director suggested the pain is felt at the top making them more receptive to a fix. Together, these signals highlighted accounts with clear need, high intent, and the right timing for automation.
Target hot accounts with strong buying signals with both the budget and need for your product.
Act quickly to book meetings within the next 10 days, as these accounts are prime for conversion right now.
Signal 1: Financial Broker Niche – Companies operating specifically in financial broking.
Signal 2: UK Geo Fit – Brokerages headquartered or operating in the UK or USA.
Signal 3: Lean Teams (<50 HC)` – Firms with under 50 employees indicating high ops-automation need.
Signal 4: Exec-Level Targets – CEO/Founder/VP/Director as primary decision-makers.
Now, let’s take a look at how the GTM Agent put this into action.
The GTM Agent targeted accounts matching the above signals and turned high-intent leads into warm conversations—without any manual follow-ups from the founder. This gave the team bandwidth to focus on closing, while outbound ran on autopilot.
Challenge: The manual, time-intensive process of finding companies actively hiring.
Solution: An AI-powered workflow implemented to automate lead identification, research, and qualification.
Let’s take a look at the flow run by the AI Agent for Juno AI
Juno AI Agent Process and Steps:
The Juno AI Agent process starts with a simple input, much like what a human SDR would begin with. From there, the AI agent searches the public web to identify companies and score & qualify as per signal criterias
Next, it identifies relevant decision-makers (Sr. Execs, Directors) and enriches their profiles with verified email addresses. Once the contacts are ready, the system automatically pushes this enriched data into your CRM or email sequencer (like Smartlead), setting the stage for targeted outbound campaigns.
This end-to-end automation helps SDR teams skip hours of manual research and focus only on high-probability conversations.
Human-in-the-Loop Campaign Management. While GTM Agents are autonomous, every campaign benefits from an expert-led human-in-the-loop (HITL) architecture that ensures precision, adaptability, and reliability—especially in complex SaaS and GTM environments where AI alone may fall short.
The campaign engine is supported by real humans with deep expertise in GTM systems, making the service resilient, customizable, and highly contextual.
What This Means for the Juno AI Team:
● No DIY configurations — Our team handles all technical setup, infrastructure, and sequencing logic.
● No risk of failure — If the AI agent cannot process a domain, extract signals, or validate contacts, our human experts step in immediately.
In this sprint we could identify 50+ accounts that are in fits show signal level hot and fits ICP fit.
GTM Agent handled large daily send volumes with zero drop in performance. Maintaining a steady 1.5% reply rate across the entire outreach window.
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