Featured case study
AI-Driven Storytelling Platform
An AI-powered platform that helps people, families and communities turn their memories into professionally designed, printed books.
Read the case study
AI chatbots, recommendation engines, computer vision and generative AI features built into apps people use every day.
Stack we work in
Figures as of Oct 2026
Trusted by
Equitysoft builds AI products and adds AI to existing ones: chatbots trained on your own content, recommendation and matching engines, image and video analysis, and generative tools that write, draw and speak.
We have shipped AI for consumer apps, field teams, courier operations and analytics platforms, so we design for real users and real data, not demos. Each build includes the app, the admin side, the model integration and the guardrails that keep answers on topic and costs under control.
Most teams can get a model to work in a demo. The hard part is a feature that real users trust, that runs on messy data and that does not cost more than it earns.
AI demos that work on clean samples but fail on real user input
Chatbots that drift off topic or answer with confident mistakes
Model and API costs that rise faster than usage or revenue
No clear way to test whether a prompt or model change made things worse
AI features bolted onto apps without a flow for errors or uncertainty
Outcomes
We build AI into consumer apps, business tools and data platforms, from a single feature to a full product.
We build AI-first apps for:
Our AI work also covers:
Our AI solutions support:
Where we put AI to work across products and operations:
Apps that write, illustrate, narrate and summarize.
Assistants that answer from your content and stay on topic.
Personal suggestions based on taste, behavior and context.
Image and video analysis for consumer and business use.
Decisions and operations backed by data and AI.
Getting models into production and keeping them reliable.
We have shipped AI chatbots, recommenders, image tools, storytelling apps and dispatch automation for consumer and business users, not only prototypes.
We build the mobile app, web app, admin panel and AI pipeline together, so the AI feature fits the product and the people who run it.
Topic limits, evaluation sets, logging and usage controls are part of the first release, so quality and spend stay visible as usage grows.
We work across OpenAI, Gemini, ElevenLabs and open-source vision models, and choose per task on quality, speed and cost.
Featured case study
An AI-powered platform that helps people, families and communities turn their memories into professionally designed, printed books.
Read the case study
AI Video Analytics CCTV Intelligence Development
AI Broadcast Radio Automation: From Prompt to Live Radio Broadcast
Building an AI-Powered Wardrobe & Style Intelligence App
Smart Skincare with Lisa
Building a Real-Time Sports Data & Community Intelligence Platform
Journey to Storybee: AI Storytelling App
Powerhouse Courier – AI-Powered Dispatch & Delivery Management Platform
BullsAI – AI Market and Talent Intelligence Platform
Create Stunning Art Instantly with AI HyperVerse
DermaQ – AI Skincare Advice Chatbot
Eaudvisor – AI Perfume Guide and Fragrance Advisor App
Enhance Your Photos with Appost’s AI Editing and Creative Tools
Recomate – AI Recommendation App for Food, Movies and Things to Do
TraideFinder – AI Stock and Crypto Market Scanner
AI Caregiving Organizer App for Families
AI and Machine Learning Web Platform
AI Personalized Storybook Creator
AI Script-to-Voice – Automated Radio Broadcast Pipeline
AI Restaurant Discovery App for Dietary Preferences
AI Sports Analytics and Match Prediction Platform
AI Life Story Book Platform with an AI Interviewer
AI Wardrobe Insights and Style Identity App
Aralia – AI Image and Chat Social App
Arihla – AI Travel Planning and Booking App
BlendTwo Smart and Secure AI Dating App
Lisa AI – Personalized Skincare Recommendation Chatbot
PetDX.ai – AI Veterinary Diagnostics and Pet Care Platform
PetXD.AI – Preventive Pet Health App with AI AnalysisWe look at your users, data and workflows and pick the AI feature most likely to pay off first.
You receive Prioritized AI use cases
We test sample data against candidate models and prompts to confirm quality before we commit to a build.
You receive Feasibility notes and model choice
We design the user flow around the AI, including loading states, errors and what happens when it is unsure.
You receive UI designs and working prototype
We build the app, admin and AI pipeline with topic limits, logging, evaluation sets and cost controls.
You receive Tested release candidate
We release, watch quality and cost in production, and improve prompts and models from real usage.
You receive Production launch and tuning plan
Tech stack
AI and machine learning
Databases
Mobile
Frontend
Backend and APIs
Languages
Cloud and DevOps
Other tools
Engagement
Pick the model that matches how certain your scope is today. Many clients start with one model and move to another as the product grows.
For a defined product, module or integration. We agree scope, milestones and acceptance criteria up front, then deliver in sprints with a demo at the end of each one.
For a new idea that needs proof before a full build. We ship the smallest version that tests your riskiest assumption, then plan the next release from real usage.
For an ongoing roadmap. Developers, QA and designers join your team, work in your tools and hours, and scale up or down as priorities change.
For live systems. We monitor, patch, update dependencies and ship improvements on an agreed monthly allocation, so the platform keeps pace with your operations.
We build AI chatbots and assistants, recommendation and matching engines, computer vision for photos and CCTV, generative tools for text, images and voice, and AI analytics dashboards. Most projects add AI to a mobile or web app, with an admin panel to manage content and settings.
Yes. We use retrieval so the assistant answers from your documents, books or knowledge base, and we set topic limits so it declines questions outside its scope. Admins can upload and update the source material without a developer.
We work with OpenAI, Google Gemini, ElevenLabs and open-source models, and we use PyTorch, OpenCV and YOLO for vision work. We pick the model per task based on quality, speed and cost, and keep the integration flexible so you can switch later.
We add input and output checks, topic limits, logging and human review where mistakes matter. We cache common requests, set usage limits per user and track spend per feature, so you see the cost of each AI call before it grows.
Yes. We often start with a proof of concept on your real data to confirm the model performs well enough. Then we build a clickable prototype of the user flow, and move to full development once both hold up.
You do. You own the source code, prompts, data, designs and IP from the project, with no lock-in. We sign an NDA before you share details, and you can keep working with us or move the product to another team.
Answers grounded in your own documents and data
Topic limits and fallbacks when the AI is unsure
Personal recommendations from preferences and behavior
Image recognition and analysis from a phone camera
Text, image and voice generation in one workflow
Admin panel to manage sources, prompts and settings
Usage limits, caching and per-feature cost tracking
Evaluation sets to catch quality drops after changes
Human review steps for high-stakes outputs
Coin, credit and subscription billing for AI features
Offline capture with AI processing when back online
Logs of AI inputs, outputs and approvals
Book a free consultation to pick the first AI feature, test it on your data and plan the build.