AI SDR
AI SDR Systems That Book Meetings, Not Spam Folders
We build hyper-targeted outbound engines that use tiny, ultra-specific lists and multi-channel sequencing. More targeting, less blasting. The exact playbook businesses use to hit $2M increase in new customer revenue.
The OLD Playbook
Your Outbound Is Broken. And Your Prospects Know It.
In a world drowning in AI slop and automated, non-personalized outreach, your emails look exactly like everyone else's. They hit spam. They get ignored. They damage your brand.
The old playbook, blast 10,000 emails, hope for 50 replies, doesn't work anymore. Buyers are smarter. Filters are tighter. And your competitors using the same templates sound exactly like you.
❌ Generic personalization: "I saw you work at [Company]" isn't personalization. It's mail merge.
❌ Single channel blasts: Email only means you miss prospects who live on LinkedIn.
❌ No signal, all noise: You're emailing CFOs and interns with the same message.
Co-founder @ One Second AI
Nuutti Räisänen
The NEW Playbook
Micro-Campaigns That Actually Convert
The secret isn't better templates. It's tighter targeting. When your list criteria is so specific that the messaging writes itself, reply rates explode.
01
Tiny Lists, Massive Relevance
Instead of 10,000 prospects in a CSV, we build lists of 10-100 that are so specific the list itself becomes the message. "Series A founders in X niche who recently hired Y role." The tighter the criteria, the more relevant your outreach.
Hyper-specific ICP targeting
Signal-based list building (funding, hiring, tech stack changes)
Automatic enrichment via Clay, Apollo, and custom scrapers
List criteria = email angle (no generic templates)
02
Multi-Channel Punch
Hit email + LinkedIn in the same short window. Connection request → accepted → personalized DM. Email lands reinforcing the same message. A "wall of sound" with quality touches.
Synchronized email + LinkedIn sequences
Timing optimized for maximum overlap
Consistent messaging across channels
03
Engager Outbound
Scrape your LinkedIn post likers and commenters, enrich them, and run a targeted sequence: "Hey, saw you liked my post on X, thought you might find Y interesting..."
Warm outreach to engaged prospects
ICP filtering on engaged audiences
Personalized follow-up sequences
04
Inbound Lead Scoring
Stop guessing which inbound leads matter. We build scoring systems that unify messy data, enrich automatically, and surface buyers ready to engage — instantly.
Behavioral + firmographic scoring
Automatic data enrichment
Real-time routing to reps
05
CRM Enrichment Engine
Turn your stale, messy CRM into a constantly updated goldmine. Solve data integrity problems for good. This is Clay's most valuable use case. and we build it custom for your stack.
Automated data cleaning & deduplication
Continuous enrichment on new records
Custom field population
06
Pre-Drafted Copy Engine
Fully automated copy generation that removes manual research. Your BDRs get pre-written, highly personalized emails ready to send, not templates to fill in.
AI-generated drafts from enriched data
Angle-specific copy variations
One-click send or edit
RESULTS
What Micro-Campaigns Deliver
Way fewer crickets. Way more actual meetings booked.
Pricing
Build Your Outbound Engine
The technical playbook, implemented for you. Not theory, actual working infrastructure.
Outbound Setup
Complete multi-channel outbound engine with AI-generated copy and LinkedIn automation.
Starting at
€5,000
/ one-time
Includes
ICP definition & list building setup
Clay workflows for enrichment
Email sequencing infrastructure
Multi-channel (Email + LinkedIn)
Engager outbound workflows
CRM integration
FAQ
Frequently asked questions
Co-founder @ One Second AI
Nuutti Räisänen
What does One Second AI actually do?
What does One Second AI actually do?
We help companies move from manual sales and marketing work to AI-first execution. That means designing the right strategy, then building and deploying autonomous AI agents that handle real workflows, like follow-ups, qualification, routing, reporting, and coordination, inside your existing systems. We don’t sell tools. We build systems that run.
Are you a software company or a consultancy?
Are you a software company or a consultancy?
Neither. and intentionally so. We work as an AI execution partner. That means we combine: - strategy - system design - hands-on implementation - continuous optimization You get working AI agents in production, not slides, prompts, or recommendations you have to implement yourself.
What kinds of companies do you work with?
What kinds of companies do you work with?
We typically work with: B2B companies Scaling teams (often €1M–€50M+ revenue) Sales & marketing teams struggling with manual work, slow pipelines, or tool sprawl Our clients usually know something needs to change, they just don’t want risky pilots or disconnected experiments.
Do we need to replace our current tools or systems?
Do we need to replace our current tools or systems?
No. Our AI agents are designed to work with your existing stack, CRM, marketing tools, communication channels, data sources, and internal processes. The goal is not replacement. The goal is orchestration and automation across what you already use.
How is this different from automation tools or AI copilots?
How is this different from automation tools or AI copilots?
Most tools: - automate individual tasks - require constant human input - don’t learn or adapt Our approach: - deploys autonomous agents, not scripts - connects multiple workflows together - operates continuously - improves based on outcomes Think less “automation” and more AI workforce.
Is this safe for our brand, data, and compliance requirements?
Is this safe for our brand, data, and compliance requirements?
Yes, governance is built in from day one. We design agents with: - brand rules - approval logic where needed - clear boundaries on actions -auditability and monitoring This isn’t experimental AI running loose. It’s controlled, production-grade deployment.
Can we start small before committing long term?
Can we start small before committing long term?
Yes, and many teams do. A common starting point is: - an AI assessment - a strategy workshop - or a focused initial deployment This allows you to validate fit and value before scaling.
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