I tested my AI search competitors. Most don't actually use AI.
For the last 6 months I've been building Queryra, a
semantic search plugin for WooCommerce. Solo, bootstrapped,
research phase. No paying customers by design (the "100
free partners vs 1 customer" model).
Last weekend I did something I'd been putting off:
I systematically tested every "AI search" competitor in
the WordPress directory. Wanted to verify what they
actually do under the hood vs what their marketing claims.
What I found was clearer than I expected.
FiboSearch. Keyword matching with fuzzy + synonyms.
The "AI" comes from an optional ChatGPT integration on top.
SearchWP. Keyword-based with engine weighting. AI
features (semantic, image, suggest) are paid add-ons
calling OpenAI for query refinement. The core is keyword.
Relevanssi. Full-text search with custom weighting.
Doesn't claim AI. Refreshingly honest.
AI Vector Search (Semantic). The most interesting case.
Default Lite Mode uses TF-IDF (keyword). Real vectors only
with paid Self-Hosted Supabase + your own OpenAI API key.
Queryra (mine). Real vector embeddings via ChromaDB
plus LLM intent parsing. Free tier. 50+ languages tested.
The marketing-vs-reality gap is wider than I assumed. Most
"AI search" plugins are keyword search with a marketing
layer on top.
This affected how I think about positioning. I'd been
playing nice. Calling Queryra "another option in the AI
search space." Now I realize: the space isn't crowded with
AI search. It's crowded with keyword search wearing AI
labels.
That's a different competitive landscape than the one in
plugin marketing copy.
For solo founders building in mature categories: it's
worth verifying that the "competitors" in your space
actually do what they claim. Sometimes the apparent crowd
thins out when you check the technical reality.
Wrote up the full methodology + side-by-side tests for
anyone evaluating AI search plugins:
https://queryra.com/blog/which-wordpress-ai-search-plugins-actually-use-semantic-search
Curious if other IH folks have found similar gaps in your
categories. Where do marketing claims and product reality
diverge most in WordPress / SaaS space?
One thing stood out to me.
Your research seems to answer why Queryra is technically different, but I'm not sure it answers why the first customer buys.
Those are often different decisions.
The risk is spending months proving the category is misrepresented while the real bottleneck sits somewhere else entirely.
I wouldn't try to solve that casually in the thread because the answer affects positioning, validation, and what signal actually matters before revenue.
If you're open to it, share your email and I'll put the tighter read together properly.
Fair observation — those are different decisions.
For context: Queryra is in research phase by design, no
paying customers yet (the "100 free partners vs 1 customer"
model I mentioned in the post). The blog post addresses
positioning vs the category, which is upstream of customer
acquisition.
What signal would you want to see before revenue? Genuinely
curious — happy to discuss in the thread.
Fair. That’s exactly where I’d be careful.
Research-stage products can easily measure interest in the thesis, while the real test is whether the buyer has enough pain to change behavior.
The right signal depends on who Queryra needs to become indispensable for.
I wouldn’t answer that loosely in-thread because the wrong signal can create false confidence.
If open, send me your email and I’ll write the tighter version properly.