AI Powered Outreach
Intelligent pipeline at scale. Not spray and pray.
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AI outreach and automated lead generation at scale
We build custom outbound pipelines: our own enrichment layer for prospect enrichment, our AI messaging engine for AI personalized messaging, and our multi channel automation layer for multi channel automation. Every message is generated from prospect signals: funding rounds, hiring patterns, tech stack, industry context.
The Difference: We do not use templates. Our pipeline generates individualized messages based on real company signals. The infrastructure is purpose built: dedicated sending domains, SPF/DKIM/DMARC configured, warmup protocols, deliverability monitoring. Outreach as a technical system, not spray and pray.
Our Outreach Delivery Process
ICP & Infrastructure
Define ICP, build prospect database, configure sending domains with full deliverability stack.
AI Enrichment
Enrich prospects with our own data layer: funding rounds, tech stack, hiring signals, and company context.
Message Generation
Our AI messaging engine generates individualized messages. No templates, no merge fields.
Launch & Optimize
Multi channel cadences on our automation layer with A/B testing and pipeline tracking.
Signal based audience matching
Generic outreach fires blind across every dimension. Our AI pipeline scores each prospect against six real time signals before a single message is sent. Funding stage, tech stack fit, decision maker seniority, industry alignment, hiring velocity, and optimal send timing.
Reply Rate
8.3%
vs 1.2% industry avg
Open Rate
67%
inbox placement verified
Meeting Book Rate
3.1%
of total prospects contacted
Response Time
2.1d
avg time from first touch
Outreach Capabilities
Custom Pipeline Architecture
Bespoke outbound stacks built on our proprietary enrichment, automation, and AI messaging layers.
Hyper Personalized Messaging
Every touchpoint generated from real company signals, not string substitution.
Deliverability Infrastructure
Dedicated domains, SPF/DKIM/DMARC, warmup protocols for inbox placement.
Multi Channel Cadences
Coordinated email and LinkedIn sequences with intelligent follow up logic.
Prospect Enrichment
200+ companies per wave enriched with funding, hiring, tech stack, and role data.
Pipeline Reporting
Opens, replies, meetings booked, and deals created. All tracked and reported.
200+ companies per campaign wave
Every prospect receives an individualized AI generated message based on their company's specific signals. Full deliverability infrastructure ensures inbox placement.
Build your outreach pipeline →const prospect = await enrich(lead);
const message = await ai.generate({
signal: prospect.recent_funding,
company: prospect.name,
tone: 'professional_technical'
});
await outreach.schedule(message);Common questions
We use our own data enrichment layer to enrich each prospect with real company signals: funding rounds, tech stack, hiring velocity, and decision maker seniority. Our AI messaging engine then generates a fully individualized message based on those signals. No templates, no merge fields. Our multi channel automation layer manages the multi step cadences, deliverability, and send timing across dedicated sending domains.
Target benchmarks from our pipelines: 67% open rate versus a 20% industry average, 8.3% reply rate versus 1.2% industry average, and 3.1% meeting book rate. Results depend on ICP quality, offer clarity, and list accuracy. We share these benchmarks transparently, not as guarantees.
We set up dedicated sending domains separate from your main domain. Each domain gets SPF records, 2048-bit DKIM keys, and DMARC policy configured. Mailboxes go through a 5 to 6 week warmup protocol before any outbound campaign begins. Bounce rate target is under 3%.
Standard tier covers 300 to 500 prospects per month with one sequence. Premium covers 800 to 1,200 prospects with two to three sequences plus LinkedIn integration and weekly reporting. Both tiers include full infrastructure setup.
Our enrichment layer sources from multiple data points: public company filings, job board posts, funding announcements, and tech stack detection via website analysis. Each data point is timestamped and weighted by recency. Funding data is scraped directly from regulatory filings and investor databases, so it reflects actual business events, not estimates. We validate decision maker information via LinkedIn cross-reference before messaging. If a prospect's employment status or company data becomes stale (someone left the company, for example), the message premise fails early enough that replies drop, and we flag the list segment for re-enrichment or removal.
Violations manifest in three categories. Policy violations occur when messaging tone, credential claims, or offer language triggers Gmail, Microsoft, or LinkedIn filters. Regulatory violations happen when outreach fails to meet local consent frameworks (GDPR in EU) or sector-specific rules (CNBV in Mexico, CBI in Spain). Data violations occur when prospect sourcing violates data privacy law or uses falsified contact information. We audit each of these during the infrastructure phase through automated policy scanning, manual compliance review by local counsel, and prospect data validation. If violations surface, we adjust message tone, source replacement prospect lists, or reconfigure data handling. 112 violations were resolved this way across our operating markets.
Every outreach campaign is integrated bidirectionally with your CRM via API connection. When a prospect receives a message, that touchpoint logs to their contact record. When they reply, click, or open, those events are captured. When they book a meeting or create a deal, those sales events are tagged as sourced from outreach. If you are tracking offline conversions (like we do in PPC), outreach feeds the same CRM events so your sales analytics can model which channel drove each opportunity. This requires infrastructure setup in your CRM, but once configured, revenue attribution to outreach becomes automatic. You can report "outreach generated 15 meetings this month, 6 of which advanced to proposal stage."
Customization happens at the enrichment layer and the compliance layer, not at campaign scale. We source enrichment data from regional databases specific to each market, so Polish company signals come from Polish registries and Czech hiring data from Czech job boards. Messaging is generated with regional communication norms factored in: Spanish prospects receive shorter sequences, Polish audiences tend toward longer technical discussion. Regulatory compliance is audited per market and configured at the infrastructure level. This adds 1-2 weeks to the infrastructure phase but reduces campaign risk substantially. Timeline impact is concentrated upfront. Cost impact is minimal because customization is configuration, not per-prospect duplication.
Why Signal-Based Enrichment Beats Template Sequences
Signal-based outreach starts with a different premise than template personalization. Instead of merging a prospect name or company into a generic sequence, our enrichment layer feeds real business signals into the AI messaging engine: when a company raised Series A funding, what technologies they are running on their infrastructure, their current hiring velocity, and the seniority of decision makers in your target persona. These signals become the foundation for message generation.
The outcome is mechanically different from template substitution. A prospect who raised Series A six months ago in the cybersecurity space and recently hired three engineers onto their platform team receives a message built around those specific conditions, not a message with their name inserted. The AI engine weighs funding recency, hiring acceleration, and tech stack alignment simultaneously. Result: a premise that is contextually acute, not artificially personalized.
This matters operationally. Template sequences succeed at some reply rates because they cast a wide net and get lucky. Signal-based sequences succeed because the premise itself is defensible. A prospect who sees a message about infrastructure decisions they actually made feels like the sender did research. A prospect who sees a name merge field in a template feels like they received spam at scale.
Compliance at Scale Across Regulated Markets
Outreach in fintech and financial services is not a copy paste exercise across markets. Compliance frameworks differ by country, and violations accumulate quietly until a regulatory body or platform enforcer (Gmail, Microsoft, LinkedIn) takes action. We resolved 112 advertising policy violations across our operating markets before engagement conclusion, with zero open violations at the end state.
The mechanics of compliance are technical and operational. In Poland and the Czech Republic, outreach must comply with GDPR data handling: prospects must have legitimate business interest documented, and consent chains matter for cross-border messaging. In Mexico and Latin America, outreach to financial services professionals carries sector-specific rules around credential claims and regulatory representation. In Spain, LSSI-CE rules apply to electronic marketing. Our infrastructure handles per-market compliance at the sending layer, not as an audit afterthought.
We configure sending infrastructure by market and maintain separate warmup protocols for each jurisdiction. Domain reputation is built independently per market because IP blocks and sender policies differ by region. This means a campaign running in Poland does not degrade sender reputation in Mexico. Each market operates on dedicated infrastructure with localized compliance attestation.
Violations typically surface in three places: policy flags from platform enforcers (Gmail, Microsoft, LinkedIn), regulatory inquiries, and accumulating bounce rates from outdated or falsified prospect data. Our approach prevents all three. We source prospect data through our enrichment layer with secondary validation, which reduces bounce rates and policy flags. We audit compliance posture before campaign launch and maintain ongoing monitoring for new policy changes.
Pipeline Integration and Revenue Attribution
Outreach success is measured end-to-end, not in opens and replies. When a prospect opens your email and later books a meeting, and that meeting closes into a customer, the attribution must track backward to outreach. This requires integration at three layers: your CRM (where leads land), your sales stack (where deals close), and the outreach infrastructure (where intent originates).
We set up bidirectional CRM integrations so every outreach touchpoint logs to your prospect records. When an email opens, that signal is logged against the prospect in Salesforce or your system of record. When a prospect replies or clicks, that event is captured. This event stream feeds your sales team's workflow without manual transfer. A prospect who receives an outreach message and books a meeting can be tagged automatically as "outreach sourced" in your pipeline.
The revenue attribution layer connects this data to outcomes. If you are also running paid media (PPC or LinkedIn campaigns), your marketing operations team can model which channel contributed to pipeline. Outreach contributes discovery and early stage awareness. Paid media contributes targeted nurturing. Together they feed your sales team a continuous pipeline. Attribution of revenue to outreach becomes possible when events are logged, deals are tagged, and closed won deals trace back to their source campaign.
This integration is operational, not aspirational. We configure the CRM API, test event payloads, and establish reporting dashboards so your leadership team can see "outreach generated X meetings this month, Y of which closed to revenue." Without this infrastructure, outreach metrics stay isolated from business outcomes.
Regional Customization in Fintech and Regulated Markets
Fintech is global, but compliance and outreach strategy are local. We operate in five core regulated markets: Poland, Czech Republic, Spain, Mexico, and Latvia. Each requires different enrichment data sources, messaging tone, and regulatory guardrails.
In Poland and Latvia, B2B outreach to fintech companies focuses on technical decision makers and requires messaging that acknowledges GDPR compliance and local banking regulation familiarity. Funding data is sourced from European databases; tech stack signals come from local infrastructure vendors and job posts. In the Czech Republic, decision maker profiles are similar, but messaging tone tends toward longer form technical discussion, so AI message generation adjusts for audience preference.
In Mexico and Latin America, outreach to fintech often targets business development and partnerships more than pure engineers. The regulatory environment emphasizes CNBV (fintech commission) compliance, so messaging must signal familiarity with local licensing frameworks. Funding data is sourced through Latin American investor databases, and hiring signals come from local job boards and company announcements. Enrichment is deeper because hiring velocity in Latin America tends to be higher relative to funding announcements.
Spain operates under EU regulations with additional local compliance considerations for credit and financial services. Messaging in Spanish requires native fluency and cultural context; our enrichment layer sources company data from Spanish registry databases and business publications. The outreach sequence length tends to be shorter (Spanish communication prefers direct pitch), so cadence is adjusted for regional communication norms.
In all five markets, regulatory compliance is baked into the infrastructure before campaign launch. This means prospect data is validated against regulatory blacklists, messaging is reviewed by local counsel for policy compliance, and sending infrastructure is configured to meet per-country deliverability standards. Outreach as a localized operation, not a global broadcast.