User-facing AI workflows
Generation, editing, summarization, analysis, and assistant-style experiences need flows that help people understand what the system is doing and why.
AI product development
AI product development that works outside the demo.
The wilder.dev team helps founders and product teams turn AI ideas into usable systems with clear interfaces, orchestration, safeguards, scoring, moderation, and backend logic around the model layer.
1 team shaping product UX and the system around the model
0-1 jump from prototype curiosity to dependable product flow
100% focus on product usefulness, not AI theater
Engagement focus
What this kind of work usually needs
The valuable part of an AI product is rarely only the prompt. It is the interface, scoring logic, storage, orchestration, and user trust built around the model behavior.
Backend orchestration and safeguards
Queueing, retries, async processing, moderation, logging, scoring, and analytics usually matter more than the first demo reveals.
Product logic around model output
A useful AI product still needs business rules, human review paths, permission boundaries, and honest fallbacks when confidence is low.
Fast iteration without fake shortcuts
We keep the implementation quick, but not in a way that leaves the team trapped in fragile prompt spaghetti later.
Core service
Start with the service behind this landing page
These service pages stay indexable and help reinforce the long-term SEO structure underneath the paid and conversion-focused pages.
AI Product Development
We help turn AI ideas into usable products with real interfaces, backend systems, moderation, and product logic around the model layer.
Backend & API Development
We build and extend backend foundations for apps that depend on clean data models, scheduled workflows, reporting, and third-party integrations.
Proof
Relevant proof from AI-backed product work
These projects show how the wilder.dev team approaches AI products when the model has to live inside a real customer experience or product workflow.
Alva — Backend and Risk Detection Engine
The Alva backend is where ingredient lists become risk assessments. Vector search matches chemicals, AI scores toxicity and exposure, and the system personalizes every result to the user's own health profile.
Reality Check
Reality Check turns AI image editing into a public gameplay loop with challenge creation, anonymous play, scoring, and leaderboard systems.
Mark Supreme
Mark Supreme brings campaign planning, AI content generation, multi-channel publishing, and analytics into one system built to keep launches moving.
Engineering notes
Useful context from the blog
These posts add search depth, technical credibility, and a stronger path from research intent into a real conversation.
How We Built Alva's Risk Detection Engine with pgvector and OpenAI
Alva's backend turns ingredient lists into personalized risk assessments using vector similarity search, multi-factor AI scoring, and health profile matching. This is how we built the detection pipeline and why we made the architectural choices we did.
Maintaining Boon across iOS, Android, and a Java backend
Boon is a good example of how everyday-looking mobile experiences can hide serious systems work underneath: VoIP intercom calls, smart access, backend coordination, and ongoing maintenance across iOS, Android, and Java.
How we usually work
A small, direct delivery loop
This is usually strongest when the product needs senior implementation judgment more than a large ceremony-heavy process.
We look at what you have
What is the product doing, where are things getting stuck, what is making development slower than it should be. Usually takes a couple of days to get a clear picture.
A plan small enough to actually start
We scope the first chunk of real work — something that moves the product forward and makes the codebase easier to work with, not a six-month roadmap.
Build, ship, keep going
The point is not just to push a release out. We want to leave things in a shape where the next release is easier too — for us or whoever picks it up next.
About the studio
Sergey Dikarev leads wilder.dev studio
wilder.dev studio is led by Sergey Dikarev — a product engineer who came up through mobile development and project management and now works across iOS, Android, web, backend, and AI products. Most of the work lives in that messy zone between product decisions and actual code: architecture, new features, fixing what slows things down, and making sure the whole thing still makes sense six months from now.
We think about the product, not just the ticket
Flows, user experience, edge cases — we pay attention to the stuff that makes a feature actually work for people, not just pass review.
Code that does not fight the next feature
Good architecture means the next thing you build lands cleanly instead of turning into a week of cleanup.
Senior engineers on real problems
The wilder.dev team is strongest on native apps, backend systems, operational software, and AI products where you need someone who has been through it before.
Relationships over one-off sprints
Our best projects run for months or years because the work keeps getting more useful, not harder to maintain.
FAQ
Questions teams usually ask first
The concern is usually not whether AI can do something once. It is whether the product can keep doing it usefully, safely, and clearly.
Do you only help with the model integration?
No. The strongest work usually sits around the model: the workflow, interface, orchestration, scoring, moderation, data handling, and product decisions that make the feature believable.
Can you help before we know the final AI feature set?
Yes. Early-stage AI work often benefits from shaping the product boundaries and fallback behavior before too much implementation hardens around a shaky assumption.
Do you work on AI products that also need web, mobile, or backend depth?
That is usually the sweet spot. The wilder.dev studio is strongest where AI is one part of a broader product surface rather than a standalone experiment.
Other tracks
Need a different delivery angle?
These related pages cover the other kinds of work the wilder.dev team handles most often.
Mobile
Mobile app development
For teams shipping iOS and Android products that need strong release discipline, offline support, smoother onboarding, or steadier product delivery.
Web + Backend
Web app and backend development
For SaaS, marketplace, internal, and operational products that need a clearer system underneath the interface before delivery gets more expensive.
Ready to compare notes?
Bring the product, the stuck points, and the next release into focus.
Share a short brief or jump into the matching work first. Either way, the next step should feel concrete and useful.