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Washington · Software directories and AI discovery

AI Discovery Platform Development for Washington Teams

People looking for software often know the task they need to solve before they know the product name. A discovery platform has to connect that intent to reliable catalogue information and a useful next step. We help Washington software-directory teams build that experience around search, editorial ownership and maintainable public pages.

Our Appster project, recorded in Mexico, combines natural-language discovery across an app catalogue, semantic vector search, administration and prerendered content pages. It shows how AI search belongs inside a broader product. Curiosive uses AI-accelerated development with engineering review and stays involved as the catalogue and its users change.

Start a partnershipFrom $2,000 per month
Concept of a software catalogue with a highlighted search result on a laptop
AI-generated concept artwork for app discovery; not an Appster product screenshot.
25
published case studies
5+
years building for production
12
countries the work runs in
100%
of code read by a senior engineer
1 day
to hear back, from the engineer
Browse industry workflows →

Build the catalogue your search can rely on

Start with representative records and the fields a visitor uses to compare products. Name the source of descriptions, categories, links and availability information, and decide who can approve a correction. A semantic search index cannot repair a catalogue that has no clear owner. Agree how duplicate products are merged, how an entry is retired and what happens when information is incomplete. Make the relationship between the search result and its public detail page explicit before expanding the catalogue.

Relevant work: Appster's AI discovery platform

The published Appster case covers natural-language discovery across more than 2,700 apps using semantic vector search over an OpenAI-embedded catalogue. It includes a full admin panel and thousands of prerendered, programmatically generated SEO pages, built with Next.js, Supabase, TypeScript and Tailwind CSS. The portfolio records the project in Mexico. Those are delivered capabilities and catalogue-scale context; they do not establish search relevance scores, traffic gains or a Washington client relationship.

Evaluate retrieval against real user intentions

Bring examples of what people ask for and the catalogue entries your team considers useful answers. Include a broad request, an ambiguous phrase, a task with several valid products and a request the catalogue cannot serve. Review retrieval quality separately from interface polish. Decide whether results need category filters, explanatory context or a conventional search fallback. Record how approved content becomes an embedding and how updates reach the index so a corrected public page does not leave stale search information behind.

Publish detail pages that help a visitor choose

A catalogue page should contain useful approved information and a clear destination for someone who wants to learn more. Plan stable entry URLs, category navigation, canonical rules and metadata around the actual content. Avoid creating several pages that make the same claim without adding a new decision or useful detail. Decide how empty categories, retired products and missing fields are handled before generating pages at scale. Page count alone does not establish usefulness or search visibility.

Review catalogue quality and discovery together

For a new engagement, bring representative catalogue records, approved descriptions and a set of user search intents. Proposed acceptance examples: each result opens the matching public record; a content correction reaches the search index through the agreed update process; an empty result offers a useful next step; and retired entries follow the agreed visibility rule. Review relevance against the approved query set separately from page rendering. These are proposed checks for your catalogue, not additional claims about Appster's search evaluation or rankings.

Keep a product partner as search and content evolve

New entries, changed descriptions and user search patterns create ongoing product work. We can maintain a shared backlog covering editorial tools, retrieval behavior and the public experience. AI helps accelerate code production and iteration, while engineers review architecture, data handling and release checks. Monthly AI-accelerated development starts from $2,000 with capacity and scope agreed in writing. Curiosive LLC collaborates remotely with Washington teams through agreed Pacific-time review windows, with engineering led from Ankara. We build a working relationship around the next useful release as well as the initial launch.

Delivered work in detail

Appster: AI app discovery with a full stack content platform

Natural-language discovery across a catalogue of more than 2,700 apps, with semantic vector search, administration and programmatic SEO pages.

Read the case study →
AI-accelerated development
from$2,000
per month

Senior engineers building your product with AI coding agents: web, mobile, SaaS or browser extension, reviewed before anything ships.

  • Web, mobile, SaaS and browser extensions
  • AI-assisted delivery under senior engineer review
  • Scope and capacity agreed in writing, renews monthly

AI-accelerated development, billed monthly. We confirm scope, capacity and start date in writing before checkout.

Questions

The things people ask before starting.

Can you add natural-language search to our existing directory?

Yes. Bring representative catalogue records, their update process and examples of useful search results. We can assess a focused search integration before deciding whether the public website or administration needs a wider rebuild.

Is Appster a Washington client project?

The portfolio records Appster in Mexico. We reference its semantic search, catalogue administration and public-page delivery as relevant work for a new Washington engagement.

Will more catalogue pages improve our rankings?

The Appster case establishes implementation scope, not a ranking guarantee. A new catalogue should publish useful approved information with coherent navigation and metadata, then evaluate results using the evidence available to your team.

Can you help keep search current after launch?

Yes. The engagement can include the approved catalogue update path, index refresh behavior and ongoing relevance reviews. Agree the content owner, evaluation examples and monthly engineering capacity in writing.

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How it starts

What happens after you write to us.

  1. 01

    You describe the product

    One paragraph on what you are building, roughly when you need it, and who it is for. No brief, no form with fifteen fields.

  2. 02

    You get a reply within a day

    From the engineer who would do the work, not a sales team. If we are not the right fit we say so, and where possible we point you somewhere better.

  3. 03

    You get a scoped plan

    Scope, price and timeline in writing before anything is committed. You decide with the numbers in front of you.

No long contract to begin, no lock-in to our tooling, and the code is yours from the first commit.

Start a conversation
Contact

Looking for an engineering partner for the long haul?

A short note about the product, the timeline and who it is for is enough to start. You will hear back from the engineer who would do the work, not a sales team.

hello@curiosive.comSee what we have shipped

Ankara / Türkiye · Working across European and US time zones