Booking Q3 2026 partner slots
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US · UK · EU · AU
We’re the build partner for marketing agencies that want to offer AI services without buying a platform or hiring an AI team. Every build ships under your agency’s brand. Most marketing-agency partners start with a chatbot or a lead-qualification automation — the highest-margin entry points for this segment. $1,500/month, including Discovery and ongoing build capacity.
A common pattern this year: a marketing agency owner gets the same question from three clients in a quarter — “what’s your AI offer?” — and doesn’t have a confident answer.
The pressure is real and asymmetric. 53% of digital agencies now view AI as a threat to their business model, while only 14% describe their pipeline as “very healthy.” The gap shows up everywhere: in flat retainers, in lost RFPs to competitors making AI claims (real or otherwise), in clients quietly building internal capabilities your agency used to provide.
Option 01
Resell platform features as your AI offer (Vendasta, GoHighLevel). Immediate line items but your differentiation collapses into your competitors’ differentiation — every agency in the platform sells the same thing.
Option 02
$180–250K loaded. Competitive market. Won’t produce client revenue for 6–9 months. Most agencies under $5M revenue can’t make this math work.
Option 03
Wins a few RFPs in the short term. Catches up with the agency the first time a client asks for an implementation timeline you can’t meet.
There’s a fourth option that we exist for. Buy the engineering capacity as a build partner instead of as a hire or a platform. Ship custom AI services under your agency’s brand. Skip the platform tax and the hiring lag.
Marketing agencies have three or four high-margin entry points into AI services. Every one of these is something we’ve shipped under a partner agency’s brand:
01 / Entry point
An AI agent that triages every inbound lead — reads the website, evaluates fit against the client’s ICP, scores priority, attaches pre-research, and routes high-fit leads to the sales team. Replaces 5–10 minutes of manual research per lead.
At even modest volume across a client’s pipeline, this is several hours per week of recovered sales-team capacity per client — billable as a service line, not just internal savings.
Most marketing agencies sell this as a $500–$1,500/month per-client service, with the bulk of the work front-loaded into setup. See AI Agents & Workflows and Automations for the full pattern.
02 / Entry point
Your client has a content library — podcast episodes, blog archive, white papers, courseware, customer support documentation. A custom chatbot trained on the corpus surfaces that content to website visitors who’d never have found it otherwise. Citation links on every answer. Lead capture activates when intent signals fire.
The live build for a marketing consultancy: 250+ podcast episodes indexed with recency filtering, generating an estimated $100K+/year in incremental qualified pipeline.
The same pattern works for any agency client with serious content depth. See the chatbot case study and AI Agents & Workflows for full detail.
03 / Entry point
A bidirectional sync between the client’s billing platform, CRM, and marketing automation closes data drift that’s silently breaking campaign segmentation.
Common version: WHMCS or Stripe to HubSpot, with full historical backfill so old customers become campaign-targetable. Recovered hours: 8–12 per week per client. Recovered campaign ROI: usually significant once product-segmented sends become possible.
See Automations for the full architecture.
04 / Entry point
Once you’ve shipped two or three of the above for clients, you’ll notice the pattern: most of your clients have the same operational problem. That’s where productization starts.
A lead-qualification bot built for one client can be redeployed for ten. A content audit agent built for one consultancy can serve every consultancy in your book.
The economics shift from “billed once per build” to “billed many times per build.” See AI Products & MVPs.
Three live builds we’ve shipped under marketing-agency partner brands:
Case 01 · Content chatbot
Custom chatbot indexed against 250+ podcast episodes with recency filtering. Citation links surfaced on every answer. Lead capture activated by intent signals. Shipped under the agency’s brand.
Case 02 · Voice AI persona
Marketing agency partner sold this as a productized service line to their legal-services clients. Voice agent self-identifies as AI, includes scope guardrails, logs all conversations, and offers opt-out to a human at any point. Three weeks from kickoff to production.
Case 03 · CRM sync
Marketing agency partner running a hosting service line for SMB clients. Recovered 8–12 hours per week of manual reconciliation. Closed a GDPR exposure on the way to becoming a problem. Unlocked product-segmented email campaigns that previously required an export-and-paste workflow.
Your client sees only your agency. We are not in your project communications, your client meetings, your delivery emails, or any system your client logs into. Your agency owns the relationship, the pricing, and the long-term revenue.
Most of our marketing-agency partners introduce us internally as “our AI team” if they introduce us at all. The work shows up under your project manager, runs through your QA, and ships under your brand. Documentation is yours. Runbooks are yours. Support email is yours. If your client asks who built it, the answer is your agency.
We’ve signed NDAs covering 100% of our active engagements. Confidentiality is the default posture, not an upgrade.
For agencies who know they need an AI service line but aren’t sure which client problem to solve first. Month one is Discovery + a roadmap. Month two onwards executes the highest-priority build from the roadmap. See strategy for what Discovery covers.
For agencies who’ve already identified a clear opportunity — usually a chatbot for a specific client, or a lead-qualification automation for the agency’s sales motion. We scope on the partner call and start the build within 1–2 weeks of contracting.
For agencies that want to validate the partnership on internal builds (lead enrichment for the agency’s own pipeline, reporting automation for client retainers) before rolling AI services out to clients. Lower-risk entry, slower revenue contribution.
Standard engagement: $1,500/month, including Discovery (month one), build capacity, deployment under your brand, source code handoff, and monthly strategy reviews.
For marketing agencies with a clear single-product MVP idea (e.g., a productized chatbot offering, a SaaS tool for the agency’s vertical), the project-based MVP Build path starts at $3,000 — quoted after scoping. Most marketing-agency partners on the monthly engagement continue iterating their productized builds for 6–12 months after MVP launch.
A typical month-one for a marketing-agency partner: Discovery in weeks 1–2, build target locked in week 3, first build in production by end of month two. About 1 in 4 engagements ships a working agent or automation in month one when the scope is clear early.
Three situations where we’d recommend against the partnership:
01 · Wrong shape
If your agency needs to spin up AI services across 50 clients next quarter and you don’t have the delivery capacity to configure custom builds for each, you want Vendasta or GoHighLevel — a platform-led model. We sell custom engineering, not configurable features. The two models solve different problems. Most agencies need both eventually; if you only need one and platform is it, we’d point you to a platform.
02 · Too early
AI service lines work when there’s an existing client base to extend. If your agency is still building its initial offer, the AI strategy work is downstream of your core positioning — which we’re not the right partner for. We’d recommend solving positioning and core service offer first, then revisiting AI in 6–12 months.
03 · Wrong filter
$1,500/month is intentionally below most custom AI development pricing because we’re optimising for sustained partnerships, not maximum margin per engagement. If price is your primary filter, a platform subscription will win on absolute cost. We win on differentiation, IP ownership, and the ability to bill clients premium for custom work.
Discovery answers this specifically, but the common pattern: start with one client-facing service (usually a chatbot or lead-qual bot for a specific client) and one internal service (usually a lead-enrichment automation for your own pipeline). Two builds, two distinct revenue paths — one billable, one margin-recovery. Most marketing agencies who follow this pattern hit AI-related revenue in 60–120 days.
No. Every build ships with complete runbooks under your brand — how to update training data, adjust scope, handle escalations, read the logs, what to do when something misbehaves. Most operational support falls into a small number of patterns documented in the runbook. For deeper issues, partners on the monthly engagement get priority support included. You don’t need an AI engineer on the team.
This is a positioning problem, not an engineering one — but it matters because most marketing agencies stumble here. The framing that works for client conversations: “We’ve added an AI service line through a build partnership. Custom AI agents and automations designed specifically for your business. Not a generic chatbot — your content, your brand, your guardrails.” The build partnership detail signals seriousness without naming us. Many of our partners use this framing verbatim.
Yes — that’s the productized-build pattern. A lead-qualification bot built for one client can be redeployed for ten with the same ICP. A content audit agent built for one consultancy can serve every consultancy in your book. We design for multi-deployment when there’s a credible resale path. See AI Products & MVPs.
Platforms sell agencies a subscription and a bundle of configurable features. We sell custom builds delivered ready to bill clients. Different solutions to different problems. Most agencies need both — a platform for commodity services and a build partner for differentiation. For the differentiated, premium-priced services your agency wants to sell, custom builds usually win on conversion quality and margin. For the high-volume, low-margin services, platforms win on cost.
Your agency built them. That’s the answer. We are not in any client-facing communication. If a client probes deeper — “did you build this in-house?” — most partners answer honestly: “We work with a build partner under NDA. The IP and engineering are ours. The relationship and pricing are with us. Confidentiality is standard in our industry.” This framing satisfies almost every client. The handful who care about the answer either accept the partnership model or self-select out of the relationship — which is fine.
Realistic timeline from contracting to first client-facing AI service in production: 6–10 weeks. Faster if you arrive with a specific scope in mind. Discovery happens in month one. First build typically ships in month two. Client-facing rollout starts month three. Agencies that want to move faster can scope a first build during the kickoff call rather than waiting through full Discovery — about 1 in 4 partner engagements works this way.
Sometimes, depending on the engagement. Our standard markets are US, UK, EU, and Australia because of language and regulatory familiarity. For other English-speaking markets (Canada, New Zealand, Singapore, South Africa, Ireland), yes. For non-English markets or unfamiliar regulatory environments, we’d discuss on the partner call before committing.
A 30-minute scoping call to look at your client base, talk through where AI services fit, and confirm whether the timing is right. No pitch deck.
Book a 30-minute scoping callA sense of which 1–2 AI services likely fit your agency first.
Rough scope and timeline for the first build.
An honest read on whether the timing is right this quarter or next.
