Paiger vs the DIY AI Stack

Claude, Clay, an outbound sequencer and a bit of Zapier or Make. Combine these in the right way and you can be on your way to building a genuinely useful, AI driven, prospecting engine for a recruitment desk. But whilst each tool is good at what it does, does the time and money spent building and maintaining the stack stack up? Especially when there are purpose built platforms that are designed to slide straight into your existing recruitment workflows. 

What's actually in a DIY AI recruitment stack

Most versions of the stacks that recruiters build use variations of the same four building blocks. The tools might change (eg. swap out ChatGPT for Claude), but the underlying principles remain the same.

Claude handles CV screening, job description writing, personalised outreach drafts, Boolean strings and interview prep. Recruiters report saving 8 to 12 hours a week using it this way. Claude Team, at roughly £20 to £25 per user a month, adds shared Projects so a firm can set tone and context once. Clay now runs as a native connector inside Claude too, so enrichment and drafting can happen from one chat window rather than two separate tools.

Clay is a workflow-automation and enrichment platform, not a recruitment product. Its waterfall enrichment runs a lookup across more than 150 data providers and merges the best result, which beats relying on any single source. Pricing runs from around £146 a month at solo scale up to several hundred pounds once a firm needs native CRM sync, and most people report a four to six week learning curve before they're comfortable with providers, credits and table logic.

An outbound sequencer (Lemlist, Instantly, Smartlead or Apollo are the common choices) sends the emails and LinkedIn messages once a list exists. They're broadly interchangeable for this purpose. None of them has any view of what's actually moving in the recruitment market, they just send what they're told to send.

Zapier or Make glues the above into something that resembles a workflow. Someone still has to design the automation, watch it when an API changes, and fix it when it breaks.

Put together, that's a real, working prospecting engine. It's also four subscriptions, four learning curves, and one person in the business who's now its de facto product manager.

Building and scaling AI in recruitment agencies

At a solo agency or a small team up to five heads, we typically see the owner builds this stack themselves. As most recruiters in this size of business are all working similar desks, builds can be kept relatively simple. The complexity comes with who builds it, though. We find that builds are typically done by a hands on business owner, on top of the day-to-day recruitment activity eg. on evenings and weekends. This is to make sure that the day to day recruitment activity doesn’t get interrupted. And if the owner is on holiday or just busy closing a placement, the whole system stops, because nobody else understands how it's wired.

At five or more heads running multiple desks, the problem changes shape rather than just growing. One person, often an ops hire or a keen consultant, builds the stack, then has to make it work across desks that don't share an ICP, a tone of voice, or a definition of a good signal. A tech desk's prompts and Clay tables don't transfer to a legal or life sciences desk, so the build effectively happens again for each one. If the builder leaves, every desk loses its workflow at the same time.

The real cost, once you price in time

"I can build this myself for less" is true if you only count the subscriptions. It stops being true once someone's time goes into the total, and it's always someone's time, whether that's the owner's evenings or a hire's working week.

Let’s break these costs down.

Solo — one recruiter

5-head — four desks

10-head — eight desks

20-head — sixteen desks

The gap doesn't shrink as an agency grows, it widens. DIY costs roughly twice what Paiger does at solo level, rising to roughly four times at five heads, five and a half times at ten heads, and seven times at twenty heads. That's because the DIY time cost scales with the number of desks being run, not just headcount, while Paiger's marginal cost per extra desk is mostly another seat, not another build.

The gap a DIY stack can't close: your CRM

Most recruitment agencies already run on a CRM, whether that's Bullhorn, JobAdder, Vincere or something similar. A DIY stack of Claude, Clay, a sequencer and Zapier has no native way into any of them. Any connection has to be hand-built, field-mapped, and maintained by whoever built it, and that gets more fragile with every extra desk pushing data through it.

Paiger integrates natively with Bullhorn, keeping signal, contact and candidate data in sync with the system of record without manual re-entry. That's not a small convenience. It's the difference between BD activity that every consultant and manager can see in the CRM, and BD activity that only exists in whoever ran the outreach.

What Paiger does instead

Paiger runs the same workflow a desk already works through, end to end: signal, research, outreach, marketing, candidate presentation, visibility. Every vacancy on the agency's website goes out as a branded LinkedIn ad automatically through Candidate Attraction. Every candidate gets a branded CV, spec email and advert in one click through Candidate Marketing. Every consultant's LinkedIn presence runs through Personal Brand & Content, voice-trained and one-tap approved, without anyone needing to remember to post.

None of that depends on one person having built and maintained it. It's live from day one, and any consultant can pick up the Day Plan whether or not they were the one who set anything up.

Do you have to give up Claude and Clay?

No. Use whichever AI assistant helps the team get through the day, Paiger adds the recruitment signal, the workflow and the CRM connection that a generalist assistant doesn't have on its own. For most recruitment BD use cases, Paiger removes the need to build a Clay workflow from scratch, though some agencies keep Clay for specialist enrichment jobs outside recruitment while Paiger runs the day-to-day desk workflow. The two aren't mutually exclusive.

The honest version of this comparison isn't AI against no AI. It's an assembled stack you have to keep building and maintaining, against a workflow that's already built around how a desk runs.