Brief drafting, research, reports, customer comms — each with per-customer brand-voice guardrails. Built for 10 to 50-person creative and marketing agencies. $3,999/mo retainer.
- Analyze
- Automate
- Monitor
monthly retainer
Who this is for
Agency owner or ops lead at a 10 to 50-person creative or marketing agency. Margins are thin, customer expectations keep rising, and the hours junior staff spend on formatting, research, and first drafts are eating into every engagement.
The pain today
- Junior staff spend 30–40% of their time on briefs, formatting, and research that follows a predictable pattern
- Customer reports pulled manually from GA4, Meta Ads, and Klaviyo take a half-day each
- Generic AI tools produce copy that sounds nothing like the customer — brand voice gets compromised
- Every new customer means rebuilding the same research and briefing process from scratch
- Margins are too thin to hire more juniors, but senior time is spent on work that should not need seniors
The outcome you get
- Brief, research, and report workflows automated on $3,999/mo retainer
- Per-customer prompt libraries that preserve each customer's brand voice across all staff
- Analytics integrations that auto-draft customer reports from live data
- Junior staff hours shifted from repetitive typing to actual creative work
- Agentic workflows that chain multiple steps — research to brief to deck outline — without manual hand-offs
Where agencies see fastest payback
Three workflows deliver clear, measurable ROI with the fewest dependencies. Brief drafting: customer intake data feeds a structured prompt that generates a strategy brief. A senior strategist reviews and refines. For agencies producing five or more briefs a week, this alone covers the retainer cost. Research summaries: competitive analysis, market overviews, and trend reports drafted from data you provide — not from AI's training memory, where hallucinations live. Research with grounded sources is accurate; research generated from thin air is not. Customer reports: analytics data from GA4, Meta Ads, and Klaviyo pulls into a report template that drafts insight summaries. Account manager reviews, adds context, sends. Manual data-pulling disappears.
I built Instill as a self-initiated AI skills platform — a structured-prompt library used across AI tools. It currently has 30+ active users, 1,000+ skills saved, and powers 45+ projects. The pattern that works there is the same one I apply to agency retainers: a shared, structured library where every team member uses the same proven prompts rather than improvising from scratch each time.
Brief, research, and report workflows automated on $3,999/mo retainer
Brand voice that holds across every customer
Generic AI output sounds generic. For agencies, that is the core problem — your output quality is the product, and a customer who notices the copy sounds flat will not renew. The fix is not more editing; it is better prompt architecture.
Each customer gets a dedicated prompt set built from their brand guidelines, tone markers, vocabulary list, and a handful of approved samples. When a team member works on that customer's content, they load that customer's prompt context. Output goes to human review before any customer sees it — that does not change. Over three to six months, the prompts improve as staff edit outputs and flag what missed. For agencies with many customers, this prompt infrastructure delivers the clearest return: it preserves each customer's voice consistently regardless of which account manager is on the brief.
+500%: Lead base growth.
Agentic workflows for multi-step agency tasks
Single-step automation — press a button, get a draft — is the obvious starting point. The bigger productivity gain comes from chaining steps without manual hand-offs. A discovery call transcript feeds a briefing template, which feeds a deck outline, which routes to the assigned strategist in the PM tool. A research task pulls competitor URLs, summarises each, and compares against customer positioning — in one run. These are agentic workflows: the AI receives a goal and executes multiple steps, adapts based on intermediate output, and delivers a finished artifact.
For agencies, the specific chains that compound fastest are: new customer onboarding (intake form to brief to project setup), recurring reporting (data pull to draft to account manager queue), and proposal research (competitive landscape to differentiator summary to talking points). None of these replace the strategist. They replace the two hours the strategist spent manually moving information between tools before the actual thinking started.
Customer-data handling and privacy posture
Agency AI workflows touch customer data — analytics, creative assets, audience segments, sometimes financial data. Three things cover the exposure properly. First, LLM providers under Data Processing Agreements with no-training terms, so customer data passed in prompts does not train future models. Second, data minimisation in prompt design — only the fields a specific task requires, never full customer records. Third, explicit AI-use language in customer engagement agreements, so customers know upfront and can consent or scope-limit.
For agencies serving healthcare, legal, or financial services customers, additional compliance applies — those verticals have specific restrictions on where and how customer data can be processed. Customers in regulated industries are increasingly asking direct questions about AI usage in their engagements. Having clean, documented answers is part of professional posture now, not a nice-to-have.
When Zapier and ChatGPT Team are genuinely enough
For agencies under ten people with general, non-customer-specific AI needs, ChatGPT Team at $25 per seat per month plus a structured prompt library covers a large share of the value. Zapier handles cross-tool automation for standard SaaS connections without custom engineering. I am direct about this because the retainer only makes sense in specific conditions.
Custom AI retainer pays back when the agency has more than one customer with distinct brand voice requirements, when PM tool and analytics integrations matter to delivery speed, or when output quality at scale affects customer retention materially. My target is 10 to 50-person agencies where the gap between generic-AI output and agency-quality output is visible in customer feedback — and where junior staff time reclaimed is enough to measurably change capacity.
Pricing, ownership, and what $3,999/mo covers
The retainer is $3,999/mo. It covers AI workflow design and engineering, per-customer prompt library builds, integrations with your CRM and PM tool, analytics connections for automated reporting, monitoring, and monthly iteration based on real usage. LLM API costs pass through at cost — typically $300 to $1,500/mo for a 10 to 50-person agency running AI across multiple customer accounts.
Fourteen-day money-back guarantee. Cancel anytime after that. Every automation I build is Work Made for Hire — 100% yours the day it ships, no licensing dependencies on me. For agencies tracking ROI by customer, I build per-customer prompt attribution so you can see which AI usage is paying back and which is marginal. Most agencies recover the retainer cost within two to four months through junior staff capacity alone — before counting new business won from faster, higher-quality deliverables.
Recent proof
A comparable engagement, delivered and documented.
A custom CRM that turned Google Maps into a lead machine
Built a purpose-built CRM for a digital agency that captures leads from Google Maps, reaches them via official WhatsApp (Twilio + Meta API), and uses AI to suggest replies and standardize templates. The system scaled the lead base by over 500%, with 250 new leads entering the pipeline every day.
Read the case studyFrequently asked questions
The questions prospects ask before they book.
Each customer gets a dedicated prompt set built from their guidelines, tone markers, vocabulary, and approved content samples. Any team member working on that customer loads the matching prompt context before generating output. Over three to six months, prompts improve as staff flag what misses the mark. The result is a consistent voice regardless of who is on the brief — which is genuinely hard to achieve with training alone.
Basic automation executes a fixed sequence when triggered. An agentic workflow gives the AI a goal and lets it plan and execute multiple steps, adapting based on intermediate output. For agencies, this means tasks like research-to-brief or data-pull-to-report draft run end to end without someone moving information between tools at each step. The strategist gets a finished artifact, not a half-done task to manually continue.
LLM providers are selected with Data Processing Agreements and no-training terms, so customer data in prompts does not feed future model training. Prompts are designed to send only what a specific task requires — not full customer records. For agencies with customers in regulated industries like healthcare or finance, additional compliance layers apply. I also recommend adding explicit AI-use language to customer engagement agreements so the posture is documented from day one.
For a 10 to 50-person agency running AI across multiple customer accounts, typical API usage runs $300 to $1,500/mo. Brief drafting costs roughly $0.50 to $2.00 per brief. Research summaries are $0.10 to $1.00 each. Report generation is $0.05 to $0.50 per report. Costs scale with volume, and per-customer attribution in the prompt setup helps track which customer work is driving API spend.
There are two modes. Summarising source material you provide — accurate, works well. Generating facts or statistics from the model's training data — unreliable, hallucinates. Agency practice is to always feed AI the actual source documents and have it summarise or analyse them. Research grounded in provided sources is solid. The skill is teaching your team the difference and building prompt templates that enforce the right mode by default.
Yes. Asana, Monday, ClickUp, Notion, and Basecamp all integrate via API. AI-generated briefs can attach to new project tasks automatically. Research outputs route to project documents. Report drafts queue to the assigned account manager. Tight PM-tool integration eliminates copy-paste between AI output and where the work actually lives. It adds two to three weeks at the start of the engagement.
Most agencies recover the $3,999/mo cost within two to four months through junior staff capacity gains alone. A team producing five or more briefs a week, pulling three or more customer reports monthly, and running regular research tasks will typically see the time reclaimed exceed the retainer cost before month three. That baseline does not count faster turnarounds that help win or retain customers — which tends to be the larger long-term effect.