GTM engineering that turns buying signals into booked meetings
We build and run outbound as an engineered system for B2B SaaS teams whose SDRs burn most of the day on manual research and data entry. You get signal-driven outreach, a CRM that stays current, and qualified meetings on the calendar, not another tool to staff.
Your pipeline runs on manual work and hope
Your reps spend most of the day on research and data entry, then send sequences with first lines that read like every other cold email in the inbox. CRM data goes stale the week after someone types it in. Pipeline rides on one or two people, and when they have a slow month, so do you. Adding another SDR to that setup buys you more of the same activity, not more qualified pipeline. The problem is not the reps. It is the layer underneath them.
How we actually build it
We treat outbound as a system of layers sitting on top of your CRM, not a list pull and a send button. A signal layer watches for funding rounds, hiring changes, and tech-stack shifts, so outreach fires on a why-now instead of a title match. An enrichment layer fills in what the system knows about each account. Claude agents score ICP fit, generate the why-now, personalize the copy, and classify every reply by intent (positive, needs context, soft pass, hard pass, wrong person). Execution runs two tracks: Apollo into Instantly for email, Dripify for LinkedIn, because your buyer does not live in one channel. Attio sits underneath as the system of record the agents read and write directly, instead of a place a human types notes after the fact. Deliverability is an engineering concern here, not a checkbox: separate sending domains, warmup, send caps, and reply monitoring are part of the build.
What you end up with
- —A signal layer that triggers outreach on funding, hiring, and tech-stack changes, not just job titles.
- —Claude agents for ICP scoring, why-now generation, copy personalization, and reply classification, each output traceable back to the signal that fired it.
- —Two-track outbound wired end to end: Apollo into Instantly for email, Dripify for LinkedIn.
- —Attio configured as the system of record, kept current by the agents instead of manual data entry.
- —Deliverability handled as engineering: separate warmed domains, send caps, and reply monitoring built in from day one.
- —A human-in-the-loop review step, so a person signs off on positioning before it goes out at scale.
Proof of Work
Digitalspoiler AI-Native PlatformSignal-Driven Sales Execution
For DigitalSpoiler, an AI-native sales execution platform, we engineered a multi-agent system that detects external buying signals in real time and turns them into context-aware outreach, combining semantic memory with live web grounding inside strict multi-tenant isolation (zero cross-account exposure). It moved the team from manual CRM workflows to signal-driven automation, with GTM strategy embedded in the workflows so outputs stay specific instead of generic. On a separate live engagement, the same architecture sources 100+ accounts a week across 14 verticals and runs 12 parallel campaigns, each mapped to a distinct ICP, with a human still signing off before anything ships.
Read the case studyCommon Questions
Automation wrecked our deliverability last time. How is this different?+
Because we treat deliverability as an engineering problem, not a volume dial. Sending domains are kept separate from your primary domain and warmed before real volume starts, and send caps plus reply monitoring are part of the build. If open and reply rates on a domain start slipping, we pull it and route around it. We would rather send fewer, better-targeted emails than torch a domain chasing send volume.
Our ICP is too niche for generic AI personalization. Won't this read like a content farm?+
Niche is where signal-driven outbound works best. We do not point a model at a name and ask it to sound clever. Each campaign is mapped to a specific ICP, and copy is grounded in a real signal (a funding event, a new hire, a tech-stack change) plus your positioning. On our live engagement we run 12 parallel campaigns, each tuned to a distinct ICP. The narrower the segment, the sharper the why-now, and the less it reads like a template.
We don't have the ops bandwidth to set this up. Is this one more tool to run?+
No. We are a sales automation agency, not a software vendor. We build the system, run it, and hand you qualified meetings and a CRM that stays current. Your team takes the calls and gives feedback on reply quality. What we need from you is access plus a few hours early on to get ICP and positioning right. After that, the operational load sits with us, not your team.
Is this an AI SDR that replaces my reps?+
It replaces the manual research and data entry, which is where reps lose most of the day, not the human judgment. Claude agents source, score, personalize, and classify replies. What stays human: the sign-off on positioning before it goes out at scale, the actual sales conversations, and any account the system flags as ambiguous. We deliberately did not automate the close. An AI SDR that books qualified meetings is useful. One that runs your deals is not, at least not yet.
We already run Apollo and a CRM. Do we rip it all out?+
Usually not. We work with Apollo, Instantly, Dripify, and Attio because that stack holds up under constant agent reads and writes, but the real asset is the orchestration and the custom signal scrapers on top, not the rented tools. If you are on HubSpot or Salesforce, we integrate rather than migrate. If a tool in your stack is actively fighting the agents, some legacy CRMs rate-limit constant access, we will tell you, and tell you why.
How long until we see meetings?+
First campaigns are typically live within a few weeks. The slow part is getting ICP, signals, and positioning right, not the plumbing. Early sends stay small on purpose while domains warm and reply classification calibrates. We do not quote a guaranteed meeting count, because that depends on your ICP size and your offer, and anyone who promises a number cold is guessing. We would rather ramp into a clean deliverability profile than burn your domains for a headline in week one.
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