Free · 3-5 days · No obligation
AI Opportunity Audit
We map your operations, find the highest-ROI automations, and hand you a ranked plan with payback math. Yours to keep, whoever builds it.
No obligation. No follow-up sequence.
AI outbound engine
An outbound engine that prospects while your team closes
Lead sourcing, enrichment, research-grade personalization and reply detection, running end to end. 5x ROI in 30 days. Or we work for free.
Teams we build for
- Hoyes Michalos
- Nurse Next Door
- Fedi
- UBC Sauder
- Merchant House Capital
- Picton Investments
- Campbell Froh May & Rice LLP
- Barnakl
- Hungerford
- Breez
Teams we build for
- Hoyes Michalos
- Nurse Next Door
- Fedi
- UBC Sauder
- Merchant House Capital
- Picton Investments
- Campbell Froh May & Rice LLP
- Barnakl
- Hungerford
- Breez
Teams we build for
- Hoyes Michalos
- Nurse Next Door
- Fedi
- UBC Sauder
- Merchant House Capital
- Picton Investments
- Campbell Froh May & Rice LLP
- Barnakl
- Hungerford
- Breez
The problems this solves
01
Manual prospecting has a ceiling.
Ten to twenty good touches a day is the human maximum. Your pipeline is capped by hours, not by market size.
02
Personalization and volume fight each other.
Templates scale but read like templates. Real research converts but takes an hour per lead. You should not have to pick.
03
Replies go cold in the inbox.
The lead answered. Nobody saw it for two days. That deal is gone and nobody can say why.
04
The agency retainer bought activity, not pipeline.
Reports full of sends and opens. Calendar still empty.
05
Your CRM is a graveyard.
Half the contacts are stale, the notes stop in March, and nobody trusts the data enough to act on it.
What we build
01 · Sourcing
Leads pulled continuously from multiple data sources matched to your ICP, instead of one-at-a-time manual research.
02 · Enrichment
Contact and company data gathered, verified and merged into one clean record per lead. No more hand-scraping.
03 · AI strategy
A custom analysis for every single lead: who they are, what they need, why you fit. This layer is what makes the next one work.
04 · Personalized outreach
Messages built from the strategy layer, not templates with a first-name token. Sent on a deliverability-safe schedule.
05 · Deck creation
Proposals assembled automatically when interest shows, personalized from the same research.
06 · Reply detection
Responses caught the moment they land and routed to a human in Slack. Intent never sits unread.
07 · Follow-up
Sequences that continue politely until there is an answer, and stop the moment there is.
Built to respect CASL: consent basis tracked per contact, sender identification on every message, a working unsubscribe, records kept.
What's included
- The full pipeline, built on your data and deployed in your accounts
- Sending infrastructure set up safely: warm-up, volume ramps, monitoring
- Your team trained to run and adjust it without us
- Monitoring, iteration and support after launch. Cancel anytime
Proof
BreezNamed with consent
Lead generation · Live
Breez takes prospect research from hours to minutes with an outbound engine
Breez spends minutes per researched prospect instead of hours, with 40+ personalized data points per proposal. The outbound engine behind it, in full.
Minutes per researched prospect, was hours
A private capital firmDescribed, not named
Private capital · In deployment
A private capital firm puts a research-first outbound engine into deployment
A private capital firm is deploying a research-first outbound engine: sourcing, enrichment, per-lead strategy and reply detection, with baselines set first.
In deploymentlead sourcing to outreach, one pipeline
Weeks, not quarters.
How the full engagement works01 Discovery
WEEK 0
02 Prototype
WEEKS 1-3
03 Deploy & train
WEEKS 4-8
04 Run & improve
WEEK 9+
How we build it
Step 01
Fix targeting before volume.
The first build narrows who gets contacted at all. Sending more of the wrong message faster is the most common way this fails, and it damages a domain you cannot easily replace.
Step 02
Earn the volume with reply data.
Drafts are graded against messages that got real replies. Volume ramps only as the reply rate holds, with warm-up and domain reputation respected.
Step 03
Close the loop into the calendar.
Reply detection routes to a person within minutes. The metric is booked calls, not sends, and the pipeline reports on that.
What we will not automate
Sending without a suppression check, and any claim in a message that is not traceable to something real about that account. We also will not buy or scrape data whose provenance we cannot explain to a client.
How it is built
See the full stackRetrieval
Every lead is researched against its own public footprint and your own history with that account, so personalization cites a real fact rather than merging a template. Past conversations are indexed so nobody gets contacted twice with the same angle.
- pgvector
- Full-text BM25
- Account history index
Agents and orchestration
Sourcing, enrichment, drafting and reply detection run as separate agents on a schedule, each with a spend ceiling. Sending is rate-limited by domain reputation, not by how fast the pipeline can generate.
- agent-worker
- browser-sandbox
- Per-agent budgets
Evaluation
Drafts are graded against messages that actually got replies before volume goes up. Reply classification is measured against a labelled set, because a missed positive reply costs more than any send.
- Eval graders
- Reply classification accuracy
- quality-worker
Models
Frontier models for research and drafting. Ordinary classifiers for reply intent and routing, which are faster, cheaper and easier to audit on thousands of messages a week.
- Frontier models, one gateway, routed per task
- Embedding models via the same gateway
- Intent classifiers
Data boundary
One lead store in your accounts. Suppression and consent are enforced in the data layer, so no agent can message someone who opted out or is already in a live deal.
- Supabase row-level security
- Suppression ledger
- No-training API terms
Named tools in this build: Claude · Apify · Instantly + HeyReach · Supabase · Slack
What that means in practice
Agents and orchestration
AI that does the work instead of just answering: looks things up, calls your systems, completes multi-step tasks, and knows when to hand off to a human.
Where we stop. Multi-agent swarms are oversold; most jobs need one well-guarded loop. If a cron job and a script solve it, that is what we build, because 90 percent per-step accuracy compounds to 59 percent over five chained steps and no framework changes that arithmetic.
Retrieval and RAG
Connecting AI to your actual documents so it answers from your knowledge, accurately and with citations, instead of making things up.
Where we stop. A dedicated vector database is justified by scale, not by default. Most of RAG quality is won or lost in chunking and indexing strategy, not in the model choice, and we have walked clients back from RAG to plain search when that was the honest answer.
Evaluation and observability
How we prove the AI actually works: measured, monitored and regression-tested like real software, not vibes.
Where we stop. There is no engagement where we skip this. The honest variable is depth: a document pipeline gets faithfulness and extraction suites, an outbound agent gets human review sampling, a classifier gets a held-out test set. We size the harness to the risk, never to zero.
Questions? Straight answers.
Also built here
Three ways in. No long discovery.
Paid · Fixed scope
First Build
One high-ROI system, built on your real data and deployed in your stack, with your team trained to run it. Fixed scope. Quoted after the audit. Covered by the 5x ROI guarantee.
Scope my first build
Paid up front. Cancel anytime after.
Free · 15 min
Intro Call
Fifteen minutes with James, not a sales rep. Bring your worst bottleneck, leave with a straight answer.
Book 15 minutes
No pitch deck.
Every first build is covered: 5x ROI in 30 days. Or we work for free. Read the full terms
Start free. Know your number in five days.
A 3 to 5 day audit of your operations, ending in a plan with the ROI math attached. No obligation.