Suits.ai is an AI platform for marketing, PR, and communications agencies. It turns a firm's own methodology, client history, and quality standards into AI agents the team uses on every account. The first agent is ready in less than 5 minutes. Benjamin Zenou is CEO and co-founder of Suits, Inc. Plans are priced by the number of client accounts, not by seat.

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The first working agent is ready in less than 5 minutes. Upload the firm's existing methods, proposal templates, or brand guidelines, then connect the client context. A full rollout across accounts takes longer. Hirsch Leatherwood, a PR agency, became fully AI-first within 30 days.

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How Hirsch Leatherwood Is Rethinking AI Retainers

Customer Case

Aug 20, 2026

Hirsch Leatherwood’s public expansion into custom AI workflows points toward more flexible B2B tech PR delivery, but turning that flexibility into profitable project work requires a system that protects scope, judgment, and consistency.

The Slack message lands at 4:47 p.m.: the client wants a new point of view, an executive byline, and a media package ready for tomorrow’s news cycle. The account lead says yes because the workflow looks faster with AI. By 9:30 p.m., the draft is technically complete, but it sounds like every other B2B tech company chasing the same story. Two senior people now have to rebuild it before morning.

Speed did not create value in that moment. It moved the bottleneck from production to review. A fast but poorly grounded workflow costs the agency twice: once in unplanned senior hours and again when the client starts questioning whether the team understands its business. When those overruns repeat across project-based engagements, the agency can appear productive while its delivery margin quietly collapses.

That is the tension behind the industry’s interest in Hirsch Leatherwood. The strategic communications firm now publicly lists GEO and “Custom AI Workflows” within its Digital Optimization services, while its content operation covers formats such as newsletters, white papers, customer stories, podcasts, video, op-eds, and speeches [1]. Its newer media arm, Hirsch Leatherwood Studios, further expands that model into multi-format editorial properties and experiences [2].

Those capabilities create the ingredients for work that can be packaged around defined projects rather than an open-ended stream of monthly activity. However, Hirsch Leatherwood has not publicly confirmed a formal transition away from retainers. The more defensible conclusion is that its visible service model illustrates how an AI-enabled B2B tech PR agency can create more modular, project-friendly delivery.

The Flexible Delivery Retainer

The answer is not to abandon recurring revenue or turn every assignment into an isolated statement of work. It is to separate continuous strategic value from discrete production work.

We call this operating model The Flexible Delivery Retainer. It has four components: a strategic core, project modules, grounded workflows, and margin gates.

1. The Strategic Core

Keep the client relationship anchored in the work that requires continuity: executive counsel, narrative development, reputation monitoring, media strategy, and senior judgment. These responsibilities benefit from retained context and should not be forced into artificial project boundaries.

The strategic core gives the agency predictable revenue while giving the client ongoing access to people who understand its market, history, and risk profile. It also prevents the relationship from being reduced to a menu of AI-assisted deliverables.

2. Project Modules

Package production-heavy work into clearly defined modules, such as a research report, product launch, executive byline program, media narrative sprint, GEO audit, or customer-story series. Each module should specify inputs, outputs, approval rounds, timeline, and the decisions the client must make.

This is where AI can materially improve flexibility. Research synthesis, first-draft development, message variation, coverage analysis, and content repurposing can move faster, allowing the agency to price a defined outcome instead of selling an ambiguous block of hours.

3. Grounded Workflows

Every module needs a controlled information layer containing the client’s approved messages, executive language, product facts, audience priorities, previous coverage, competitive context, and prohibited claims. AI should work from that client-specific foundation rather than from a blank chat window.

Grounding is what separates a reusable agency workflow from a clever prompt. Without it, the team saves time on drafting but loses that time checking facts, correcting tone, and explaining why the output missed the client’s actual position.

4. Margin Gates

Set a delivery budget for every module and create review gates before work moves into expensive senior stages. A margin gate can be as simple as checking actual hours, revision count, missing inputs, and remaining scope at the research, draft, and final-approval stages.

AI does not remove the need for operational discipline. It makes that discipline more important because faster production can conceal uncontrolled review cycles, extra versions, and undocumented client requests.

The Hidden Cost of Skipping the Framework

Consider a B2B tech agency selling a launch package for $18,000. The scope includes messaging, one press release, two executive bylines, a media list, pitch development, and launch-week support.

The agency budgets 120 hours at an average internal cost of $75 per hour. That creates a planned delivery cost of $9,000 and a 50% gross delivery margin.

Then the workflow starts without approved source material:

The AI-generated messaging contains three unsupported product claims.
The account director spends six hours correcting the narrative.
Two executives produce conflicting revisions, adding eight hours.
The media list requires five hours of manual cleanup because the targeting criteria were never defined.
The client asks for two unscoped byline rewrites, adding 14 hours.
The launch team spends seven hours reconciling different versions of the brief.

That is 40 additional hours, or $3,000 in unplanned delivery cost. The project’s gross delivery margin falls from 50% to approximately 33%.

The more damaging cost may arrive later. The client remembers the conflicting drafts, the factual corrections, and the late-night approval scramble. Even if the launch goes live, confidence in the agency’s process has weakened.

Project-based work does not become profitable simply because AI generates assets faster. It becomes profitable when the agency controls the information, decisions, and revisions surrounding those assets.

How Suits.ai Operationalizes the Flexible Delivery Retainer

Suits.ai allows an agency to turn each part of the framework into a repeatable, client-specific operating system.

Preserve the strategic core with Client Context Intelligence

Suits.ai can connect the client’s messaging, audience insights, past deliverables, campaign history, and relevant internal or external sources into a persistent context layer. The agency does not have to reconstruct the client’s worldview every time a new assignment begins.

That retained intelligence helps strategists spend less time finding background information and more time deciding which narrative is credible, differentiated, and timely.

Build project modules with workflow templates

The platform includes more than 60 workflow starting points and supports custom process-to-AI workflows. An agency can turn its launch process, media research method, byline system, or customer-story methodology into a defined sequence of inputs, AI-assisted steps, human approvals, and deliverables.

The workflow can require an approved brief before drafting begins, route claims to a human reviewer, and stop production when required client inputs are missing. This prevents “faster” from becoming a synonym for “less controlled.”

Protect voice with style-book and brand controls

Client voice should not depend on whether the person drafting the asset remembers a six-month-old messaging meeting. Suits.ai can embed the client’s language patterns, positioning, terminology, and editorial rules into the workflow.

AI accelerates the first version, but the output remains subject to human strategic and editorial review. The goal is not to automate judgment. It is to stop senior people from repeatedly repairing avoidable voice and context errors.

Protect accounts with client data isolation

Each client’s information remains separated from other client environments and is not used to train external models. That separation matters for PR agencies handling unreleased products, embargoed announcements, executive communications, and competitive intelligence.

It also gives the agency a cleaner foundation for scaling workflows across accounts without allowing one client’s messaging or confidential information to contaminate another’s output.

Monitor margin through the dashboard

A project workflow should make operational drift visible. The team can monitor where assignments stall, which approval stages create rework, and which deliverables repeatedly require more intervention than planned.

That data gives agency leadership a basis for changing the scope, workflow, or price before an underperforming project structure becomes standard practice.

Proof Point: What the Operating Model Can Change

Consider an illustrative agency producing 20 research-led content or media assignments per month.

If structured workflows reduce research, briefing, first-draft preparation, and revision administration from six hours to three hours per assignment, the agency recovers approximately 60 hours per month. At a blended internal cost of $100 per hour, that represents $6,000 in monthly delivery capacity.

Those hours should not disappear into a promise of unlimited output. The agency can reinvest them in stronger executive counsel, deeper source development, better media relationships, or additional paid projects.

This is an illustrative operating scenario, not a reported Hirsch Leatherwood or Suits.ai customer result. The actual gain depends on workflow complexity, data quality, review standards, and the agency’s current level of process discipline.

The Day-to-Day Workflow for Project-Based B2B Tech PR

1. Qualify the assignment

The account lead identifies whether the request belongs inside the strategic retainer or requires a separate project module. The human decides the business objective, reputational risk, intended audience, and definition of success.

AI can summarize the request and compare it with the agreed scope, but it should not make the commercial decision.

2. Lock the project brief

The team records the deliverables, source materials, approvers, revision limit, deadline, and exclusions. The workflow does not begin until the required inputs are present.

AI can identify gaps, such as an unsupported claim or missing executive perspective. The account owner decides whether to pause, proceed with assumptions, or revise the scope.

3. Assemble the client context

The workflow retrieves approved messaging, previous announcements, product documentation, competitive information, brand voice rules, and relevant media coverage. For a new client, a strategist validates the material before it becomes reusable context.

This step prevents every project team from conducting the same background search from scratch.

4. Run AI-assisted research

AI accelerates source discovery, coverage review, theme clustering, competitor comparison, and initial media segmentation. A human researcher verifies sources, removes weak evidence, and determines what is actually relevant to the client’s position.

No factual claim moves into client-facing work without a traceable source or approved client documentation.

5. Generate the structured first draft

The agent produces a draft using the agency’s methodology, the approved brief, and the client’s style book. Depending on the module, that output might be a message map, byline, media brief, launch plan, pitch angle, or GEO content outline.

The strategist then evaluates the argument, timing, differentiation, and potential reputational consequences. AI produces a starting point, not the final strategic decision.

6. Pass the margin gate

Before senior review, the project owner checks actual effort against the delivery budget. Unexpected requests, missing inputs, or extra revision cycles are surfaced while there is still time to protect the margin.

If the project has moved outside the agreed scope, the account lead documents a change order rather than quietly absorbing the work.

7. Complete human editorial and risk review

A senior PR professional verifies facts, claims, names, quotations, embargo details, and media relevance. This reviewer also asks the question AI cannot answer responsibly on its own: “Should the client say this publicly?”

The final approval remains human because the agency owns the recommendation and the relationship.

8. Deliver and capture learning

The finished asset is delivered with its supporting sources and agreed success measures. After completion, the team records which angles worked, which revisions repeated, and where the workflow slowed down.

Those learnings improve the next project without allowing one client’s information to cross into another client’s environment.

Flexibility Needs an Operating Standard

Hirsch Leatherwood’s public investment in custom AI workflows, GEO, and multi-format content reflects a larger opportunity for B2B tech PR agencies. Firms can sell more focused projects, move faster around market moments, and give clients clearer choices without discarding the strategic continuity that makes PR effective.

But the commercial model must mature with the technology. The agencies that protect their margins will not be the ones generating the most content. They will be the ones that define scope clearly, ground every workflow in client context, preserve human judgment, and measure where delivery effort actually goes.

Book a Suits.ai demo to see how your agency’s methodology can become a controlled, client-specific workflow.

Frequently Asked Questions

How is a B2B tech PR agency using AI to transition from retainers to project-based work?

A B2B tech PR agency can use AI to standardize research, briefing, drafting, media analysis, and content repurposing inside defined project modules. The agency keeps strategic counsel and relationship management in a recurring core while pricing launches, reports, executive content, GEO programs, and campaign sprints as separate projects.

Publicly available information shows Hirsch Leatherwood offers custom AI workflows, GEO, and an extensive content studio, but it does not confirm that the firm has formally replaced retainers with project-based pricing [1].

Can AI make project-based PR work more profitable?

Yes, when AI reduces repeatable production time without increasing review time or scope. Profitability depends on approved inputs, reusable client context, revision limits, human approval gates, and project-level margin tracking.

If AI produces generic or inaccurate material, senior staff must repair it. The agency may deliver faster on paper while earning less on the engagement.

Should a PR agency replace retainers with project-based pricing?

Not entirely. Retainers remain useful for executive counsel, reputation management, narrative continuity, media relationships, and rapid-response support.

A hybrid structure is often stronger: retain the ongoing strategic layer, then price production-heavy campaigns and deliverables as scoped modules. This gives the client flexibility without forcing the agency to provide unlimited work for a fixed monthly fee.

What PR agency work should be automated with AI?

AI is well suited to research synthesis, coverage categorization, briefing, first-draft development, message variation, content repurposing, and reporting preparation. These tasks are repeatable and can be governed by clear inputs and review criteria.

Humans should continue to own strategic recommendations, source verification, relationship decisions, sensitive communications, final editorial approval, and reputational risk.

How does Suits.ai help PR agencies manage project-based client work?

Suits.ai turns an agency’s methodology into client-specific workflows containing approved data, brand voice, task sequences, and human approval points. Its workflow templates and agent builder accelerate repeatable execution, while Client Context Intelligence and data isolation help keep outputs relevant to the correct account.

The platform can also support branded client-facing applications, allowing agencies to productize parts of their expertise without giving up control of the underlying process.