Proprietary technology
Intelligent agents, automation systems and content generation we build and run ourselves, not a thin layer over someone else’s API.
We start with opportunity research. If AI does not pay back on your task, we will tell you so.
Swipe your pipelines.
Space to scale.
Intelligent agents, automation systems and content generation we build and run ourselves, not a thin layer over someone else’s API.
The models are configured by people who have run campaigns, so the output is judged by whether it sells, not by whether it reads well.
Every system is designed against a specific business task and integrated with the tools your team already uses.
![The U [in] AI lab designing an acquisition system](/img/what-we-are.webp)
Run one on its own, or stack all three so a prospect meets the same brand on LinkedIn, in the feed and in the inbox.
Outreach run end to end — from the account list to a booked meeting
The core engine. We define the ICP, find and enrich the accounts, write and send personalised outreach, qualify the replies and hand you a calendar invite. You pay for the meetings, not for the activity.
Get a quoteConduct an in-depth marketing briefing
Define your ICP and client targeting criteria
Audit your LinkedIn accounts and optimise them if needed
Connect your accounts to the U [in] AI platform
Create a dedicated AI agent for your project
Develop the communication strategy and conversation flows
Launch the campaign and start identifying potential clients
Analyse results and continuously optimise the campaign
Your LinkedIn presence, run by AI + human editors
Leads always check who is writing to them. We keep your company page and founder profile alive and credible: content plan, post writing, visuals and scheduling — so every prospect who opens your profile sees an active, trustworthy brand.
Get a quoteDone-for-you email outreach that turns cold contacts into meetings
We design, write and run targeted email campaigns for your product — from sending-domain setup and warm-up to copywriting, delivery and reply handling. Works standalone or as a second touch for the leads we reach on LinkedIn, so no interested prospect slips away.
Get a quoteSoftware, medtech, logistics, healthcare, FMCG, biotech, foodtech. The industry changes; the way we build the flow does not — which is why it adapts to almost any market.

70%
of all leads delivered were approved by the client as qualified
Only 30% were rejected. The campaign achieved strong targeting accuracy and created a stable flow of relevant opportunities in one of the most competitive B2B industries.

130%
of planned sales in the first quarter in South America
This success came from precise targeting and enhanced sales efficiency, enabling rapid market penetration and performance beyond expectations in a competitive market.

+15% / +25%
sales on the US–Asia route, and conversion efficiency
Lead management improved, opening new market segments and boosting trans-Pacific revenue. U [in] AI’s data insights improved strategic decisions in the challenging US–Asia logistics market.

30+
meetings with targeted clients globally within a month
The result surpassed expectations and established a strong base for further business growth. U [in] AI’s role in navigating the global healthcare market and connecting the company with significant potential partners has been instrumental in their ongoing success.

4 → 7
deals a month closed by the same two-person sales team
By delegating pre-sale engagement to U [in] AI, the team raised its output without additional resource strain.

120+
leads ready to discuss partnerships, within three months
The network was built from a screened base of 32,700 businesses, narrowed to 6,400 targets and 9,700 decision-makers with negotiating authority.

10
contracts secured within three months — 40% faster than previous market entries
This efficiency demonstrated U [in] AI’s role in fast market penetration and establishing a strong early presence in a competitive market.
Send a request and we will share a relevant example — with the numbers behind it.
Every one of these is a process problem before it is a technology problem. That is where we start.
See the tasks we are asked to automate

Lists rebuilt by hand, messages rewritten one by one, reports assembled from five tabs. Volume that grows with the team instead of with the pipeline.
Reaching ten times more people means ten times more people writing. The channel works — the process does not stretch.
The best copy, the best qualification calls and the best judgment live in two or three heads and leave when they do.
The more hands touch the content, the less it sounds like one company. Generic AI output makes it worse, not better.
By the time the numbers are collected and interpreted, the campaign they describe has already finished.
Manual steps cost money and still miss things — a lead not followed up, a segment never tested, a reply left for Monday.
The full technology perimeter of U [in] AI. Most projects use a few of them; all of them are ours to build and run.
![Engineer configuring an AI agent inside the U [in] AI platform](/img/solutions.webp)
Every service, on its own page
We start by finding where AI actually pays back in your marketing — and where it does not.
The architecture of the system: what it decides, what it drafts, what stays with your team.
The expertise of your founders and specialists captured as a model that keeps working when they are busy.
Agents that run a task end to end — research, outreach, qualification, follow-up — and hand you the outcome.
Content produced at volume in your tone of voice, from social posts to sales collateral.
The system plugged into your CRM, your channels and your reporting, not parked beside them.
Campaign operations and optimisation handled by the system, with decisions surfaced for approval.
Your people trained on the system they will own, so it does not depend on us to keep running.
Monitoring, tuning and updates after launch — models drift, channels change, the system keeps up.
Audiences, data and communication handled by the agents across LinkedIn and email. Three steps — you only judge the last one.
We read company sites, open roles and hiring signals — not just LinkedIn keywords — and build the list against your ICP. Anyone already in your CRM is dropped before you ever see them.
Top 3–7% of leads vs. standard databasesSeveral value propositions run against several segments at the same time. Two weeks in, the combinations that nobody answers are retired and the budget moves to the one that works.
8–12 A/B tests in the first two weeksEvery lead reaches your panel with the whole conversation attached. Accept it and it goes to your CRM; appeal it and you are not charged. Nothing is billed before you look at it.
You review each lead before it is chargedDigital twins, tone of voice and content automation working as one scenario instead of three separate tools.

Digital twins hold the expertise and the tone of voice; the agents apply them across every channel where your company speaks.
Talk it through with usMarketing operations is where automation compounds: the same decisions, made faster and logged every time.

Campaign management, optimisation and decision support run as part of your existing process — the system proposes, your team approves.
Talk it through with usWhen the task has no product to buy, we design and build the system from research to support.
What the business actually needs solved, and what success looks like in numbers.
How the system is put together — data, decisions, hand-offs, guardrails.
The models that fit the task, the languages and the cost per operation.
We build it on our own technology stack, not on a no-code assembly.
Wired into your CRM, channels and internal tools.
Run against real cases until the output is good enough to act on.
Your people learn to operate and adjust the system themselves.
Ongoing monitoring and tuning once it is live.

The same route on every project, so you always know what is happening and what comes next.
Where AI pays back in your marketing.
The system architecture and the rules it works by.
Building and configuring on our own technologies.
Into your CRM, channels and reporting.
Against real tasks, until the output is usable.
Your team takes ownership of the system.
Monitoring, tuning and updates after launch.
A generic model produces generic marketing. We embed the expertise of your founders and teams into the agents and digital twins, so the system carries your knowledge and your tone of voice.
Institutional knowledge stays in the company even when the people who built it are unavailable.
The system fits the way your team already works, including the approvals it has to pass.
Content sounds like your company, not like a language model with a brief.
Specialists stop doing the repetitive part and spend their time where judgment matters.

The scenarios we are asked for most often, in B2B and B2C alike.
![B2B and B2C acquisition scenarios run by U [in] AI](/img/use-cases.webp)
Find the accounts that fit, reach them, qualify the replies.
Audience, data and communication handled as one funnel.
Volume content in your tone of voice, across formats.
Continuous presence without a permanent editorial team.
Sequences drafted, personalised and followed up automatically.
Campaign management and optimisation with decisions logged.
Briefs, reports and routine coordination taken off the team.
Company knowledge answered on demand instead of chased in chats.
Six things that decide whether an AI project ends in production or in a slide deck.
The agents, automation and content systems are ours — we can change them for your task.
Built by people who have run marketing, not only by people who have trained models.
Every system is designed around one company’s task, data and tone of voice.
The system carries your expertise and hands judgment calls back to your team.
It works inside your existing stack and processes from day one.
Volume grows without adding headcount, and we keep the system tuned after launch.
![U [in] AI team running an outbound campaign for a client](/img/why-us.webp)
Thirty minutes. We map your ICP live and show what the first batch would look like.