The specialist AEO and GEO agency, with our own AI search monitoring platform.
Focus vertical — HR Tech.
We track how ChatGPT, Claude, Gemini and other LLMs describe your product, diagnose what is holding you back, then execute the answer engine optimisation work end to end. Built on AI monitoring tool we developed in-house and configure around your category, competitors and ICP.
HR and talent leaders now build their shortlists inside ChatGPT and Claude before they ever land on your website.
Answer engine optimization and generative engine optimisation are the layer where those consideration sets get formed, and it is the layer where most HR tech companies have no presence, no data and no plan in place.
You rank on Google but you do not exist in AI search.
Search rankings and AI visibility run on entirely different signals, and ranking well on Google gives you almost no head start in AI search. Language models do not read search results pages. They draw on their training data, on third-party citations and on how clearly your product is described across the web, which means you can hold page one on Google and still be completely absent from ChatGPT, Claude and Gemini responses.
I compares you to the wrong competitors.
You do appear in answers, just grouped with tools you would never describe as competitors. The category signal you give off across your site and external sources is weak or contradictory, so language models default to placing you in the wrong comparison set. That happens at the exact moment an HR or talent leader is deciding who to evaluate, consider or choose, which is arguably more damaging than not appearing at all.
Your product gets described inaccurately.
AI models describe your features, integrations and compliance posture based on what they have learned, and what they have learned is often outdated, incomplete or wrong. Bias audits get overlooked and integrations get left out. All of this is shaping how buyers perceive your product before you have had a chance to say a word about it.
Your visibility swings between queries.
You show up in some AI responses and are not present in others, even for near-identical prompts. Your brand signal is too inconsistent for AI systems to include you with confidence, so two recruiters who phrase the same question slightly differently end up with two completely different shortlists, and yours often only makes one of them.
The signals that decide whether AI recommends you.
HR tech has a particular set of signals that drive visibility in AI search and the accuracy of how AI describes you. These are the six we track, diagnose and improve through our monitoring platform.
01
Competitive set accuracy.
Which tools is AI grouping you with, and are they the competitors that actually matter for your ICP? When the grouping is wrong, you are being evaluated in the wrong context and very likely losing to alternatives an HR buyer would never have considered if they had asked the right question.
02
Category positioning.
Does AI understand which category you belong to? HR tech categories are fragmented and constantly overlapping, and when language models cannot confidently place you in one, they tend to leave you out altogether. A clear, consistent category signal is the foundation everything else sits on top of.
03
Compliance, capability and integration accuracy.
Are your core features, integrations and compliance credentials described correctly across AI responses, or is something getting lost in translation? In HR tech, inaccurate attribution around bias, privacy and security erodes trust before a demo is ever booked.
04
Customer and use cases fit.
Do AI responses connect your product to the use cases and hiring scenarios that actually convert? Presence in "best tool for X" answers, where X matches your ICP, is the point at which AI search starts feeding pipeline rather than vanity impressions.
05
Segment and company-size fit.
Are you being recommended to the right segment? SMB, mid-market and enterprise HR teams ask AI very different questions in very different ways, so when AI puts you in front of the wrong segment, your AI presence ends up attracting leads your sales team cannot close.
06
Share of Voice versus key rivals.
How often do you appear against the three to five competitors who matter most? Share of Voice in AI search is the most direct read on how likely you are to be recommended, and it tends to be a leading indicator of pipeline health a quarter or two ahead of the funnel.
A monitoring platform that is built around your HR tech category. We do not offer just a generic template.
We built our own AEO monitoring platform in-house, and we configure it around your product, category, competitive set, positioning and the queries your HR buyers actually run. The competitors we track are the ones you actually compete with, and the metrics we surface map to how AI search visibility translates into pipeline in your specific niche.
We are a full-cycle agency, which means we do not hand over a dashboard and walk away. We analyse, we diagnose, we build the roadmap and we execute, either alongside your team or as a fully outsourced function.
Custom prompt library.
Tell us the segments you want to monitor, generate prompts automatically and pick the ones that fit, or upload your own. You get a fully configured AEO monitoring dashboard built around the segments that matter to your business, not a default one.
Configurable Niche metrics.
Mention Rate, Share of Voice, Average Rank, Competitive Set Accuracy, GEO Score and several others, all weighted and reported against the goals you actually care about. The dashboard is customisable from the ground up, so the view your team logs into reflects how your business measures success.
Adjustable competitor lists.
Nobody knows your real competitor set better than you do, and AI knows even less than that. You can adjust the brands you want to monitor and benchmark against at any time, on your terms and at the cadence that suits your sales cycle.
Full setup support by our team.
As a full-cycle AEO and GEO agency, we are involved from step zero. We set the tool up, tailor it to your category and ICP, and guide you through prioritising the GEO initiatives that will move the needle first. Execution can run with your team, with ours, or with a blend of both, depending on the bandwidth and capabilities you have in-house.
Execute with your team or with our support, depending on your internal capabilities.
We adapt monitoring and AEO implementation to your category, internal metrics, and workflows.
We adapt monitoring and implementation to your category, your internal metrics and the workflows your team already uses. Strategy, execution and our in-house monitoring platform run as one engagement, so the work shows up in AI search visibility you can actually measure.
4 STEPS
AEO monitoring,
Monitor AEO – if & how you appear in AI search:
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mention rate,
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share of voice,
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brand attribute signals,
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topic coverage matrix,
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brand & source co-occurrence,
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your brand GEO score & dynamics,
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& any other tailored criteria.
Learn how AI systems describe:
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your product & pricing perception,
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implementation complexity,
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enterprise readiness,
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compliance & data privacy,
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candidate experience,
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& not limited to.
1
GEO readiness,
Analyse your GEO readiness:
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own resources programming layer,
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own resources content layer,
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third-party medical presence,
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clinical and regulatory citations.
Check competitor visibility:
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who gets recommended,
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in what contexts,
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with which attributes,
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how positioning changes over time.
Understand which sources influence AI outputs:
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review platforms,
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media mentions,
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documentation,
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forums, Reddit, LinkedIn,
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analyst reports, knowledge bases, etc.
2
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quick-win identification,
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authority signal prioritization,
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content & documentation recommendations,
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external visibility opportunities,
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phased execution framework,
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our team support,
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dynamics tracking.
Get a 90-Day GEO Roadmap.
3
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website & semantic structure recommendations,
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product and solution pages optimisation,
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docs & knowledge base optimisation,
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AI-oriented content strategy,
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content creation & placement automation,
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review platform visibility increase,
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external mentions & authority building,
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Reddit, LinkedIn & community presence,
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competitive positioning optimisation.
Enjoy Generative Engine Optimisation Support
4
What GEO fixes look like in practice.
These are the patterns that come up repeatedly across HR tech engagements. The specifics shift from category to category, but the mechanics behind the fix stay consistent.
"We appear in AI answers but we are grouped with tools we don't actually compete with."
Correcting the competitive set.
GEO Fix:
When category signals are inconsistent across the company's website, external profiles and third-party mentions, AI models draw from contradictory inputs and fall back on generic groupings. The fix involves aligning category language across owned and external surfaces, building use-case pages targeting the right comparison queries and updating Crunchbase, G2 and LinkedIn profiles to reinforce the correct positioning.
What to expect: competitive set accuracy improves as consistent signals replace the contradictory ones. With aligned language across owned and external sources, the shift typically becomes measurable within six to ten weeks.
"ChatGPT keeps describing our compliance and bias controls incorrectly"
Fixing compliance and trust signals.
GEO Fix:
Thin, inconsistently structured trust and compliance pages rarely get cited by external sources, so AI models fill the gaps with outdated information inferred from competitor pages and review sites. The fix involves rebuilding security and compliance documentation as citable, structured content blocks, adding FAQ schema, publishing bias-audit and data-privacy content and distributing the corrected information through trusted third-party channels.
What to expect: compliance and trust descriptions in AI responses improve as the structured content gets indexed and picked up externally. Four to eight weeks is a typical window before the correction becomes visible in monitored responses.
"We never appear when someone asks AI for a recommendation in our category."
Building category presence from 0.
GEO Fix:
Strong SEO performance does not automatically translate to AI presence. When brand signals are too thin or too scattered, language models cannot include a product in category shortlists with any confidence. The fix involves building category landing pages around consistent terminology, creating comparison and "best tool for" content targeting high-intent prompts and expanding external authority through HR publications, expert contributors and review platform updates.
What to expect: category presence builds incrementally as signals accumulate. Brands starting from near-zero typically see measurable improvement in AI-generated shortlists within eight to twelve weeks of a coordinated push.
"Our visibility across ChatGPT and Claude swings wildly from one query to the next."
Stabilising multi-LLM visibility on symptom-led prompts.
GEO Fix:
When different language models return different descriptions and different competitive sets for near-identical queries, the root cause is usually semantic inconsistency across the website, metadata and external mentions. The fix involves standardising terminology, improving internal linking between related topics and setting up continuous monitoring across ChatGPT, Claude, Gemini and Perplexity to track variations and respond to them as they emerge.
What to expect: stability improves as the underlying signals become more consistent across sources. Monitoring is essential here as without a baseline across multiple LLMs it is difficult to tell whether changes are having any effect.
Who we work with:
Our AEO and GEO work spans applicant tracking systems, recruitment automation platforms, candidate screening and AI assessment tools, sourcing and talent intelligence products, HR and people analytics platforms, onboarding software, employee engagement and experience tools, performance management systems, payroll and HRIS platforms, learning and development tech, contingent workforce and staffing tools, and background-check and compliance products.
In marketing since 2009. In AI search since it became a category.
Our team has worked with international brands across SaaS, e-commerce, fintech and professional services for over fifteen years, originally as ContActive Tech Communications.
Today, that same senior team applies its strategic and technical expertise to answer engine optimisation, generative engine optimisation, and AI search visibility.