Powered by Chatlivo Machine Learning Development Services | ML Company
Our Services

Incubating a culture of innovation & creativity

    OUR PRODUCT

    AI Customer Engagement Platform

    AI-powered live chat and chatbot that turns visitors into loyal customers.

    Capture more leads, automate conversations, and grow your business 24/7.

    Try ChatLivo Free
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    Our Solutions

    Tailored digital products for your business growth

      OUR PRODUCT

      AI Customer Engagement Platform

      AI-powered live chat and chatbot that turns visitors into loyal customers.

      Capture more leads, automate conversations, and grow your business 24/7.

      Try ChatLivo Free
      REVIEWED ON
      award1 award4 award3 award5
      Our Work

      Explore the digital products and success stories we have built.

      DapkeSocial video app with live streaming and PK battles. Lika Real EstateProperty discovery platform for listings and leads. BurpoutSocial fitness challenges that keep people moving. ChatLivoConnected customer communication SaaS workspace. EmoTalesAI storytelling adventures designed for children. EarnifyTrack Income from Multiple Sources with Analytics & Tax Planning.
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      OUR PRODUCT

      AI Customer Engagement Platform

      AI-powered live chat and chatbot that turns visitors into loyal customers.

      Capture more leads, automate conversations, and grow your business 24/7.

      Try ChatLivo Free

      Machine Learning Development Services & Solutions

      Primocys designs and develops custom machine learning systems for prediction, recommendation, forecasting, classification, anomaly detection, and intelligent product features. We work across the full ML lifecycle—from preparing usable data and validating models to integrating inference into production software and monitoring performance after launch.

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      Core Machine Learning Capabilities

      The Engineering Capabilities Behind a Production ML System

      Services describe what you can hire Primocys to build. Core capabilities describe the technical work underneath those services: turning raw data into useful signals, selecting and validating models, serving predictions reliably and detecting when model behavior changes after deployment.

      Data Preparation & Feature Engineering

      Clean, transform and structure training data; handle missing values, categorical variables and outliers; and engineer features that represent the business problem without leaking future information into training.

      Model Selection & Experimentation

      Compare suitable statistical, classical ML and deep-learning approaches against a meaningful baseline instead of choosing a model because it is fashionable or unnecessarily complex.

      Validation & Evaluation Design

      Select metrics and validation strategies around the real decision the model supports, including class imbalance, time-based splits, ranking quality, calibration and business-relevant error costs.

      Training & Optimization

      Build reproducible training pipelines, tune model parameters and control the trade-off between predictive quality, inference speed, infrastructure cost and maintainability.

      Inference & Model Serving

      Expose models through batch jobs, APIs or event-driven services with versioning, validation, latency targets, fallbacks and application-level integration appropriate to the product.

      Why Primocys

      Why Primocys Can Build Production-Ready Machine Learning Solutions

      Machine learning development requires more than training models. Primocys builds complete ML solutions with data pipelines, model development, APIs, cloud deployment, monitoring, and seamless product integration for real-world business applications.

      Founded in

      2018

      Since 2018, Primocys has been building web, mobile, SaaS, backend, and AI-powered software products. That engineering experience helps us design machine learning systems that are secure, scalable, and production-ready.

      Production ML Experience

      We build and operate our own AI-powered products alongside client projects, giving our ML engineers hands-on experience in recommendation systems, conversational AI, model deployment, production monitoring, and continuous improvements across.

      ChatLivo Logo

      ChatLivo

      AI-Powered Live Chat for Businesses

      ChatLivo AI product interface
      EmoTales Logo

      EmoTales

      AI Stories & Learning Companion for Kids

      EmoTales AI learning app interface

      End-to-End ML Development & Deployment

      We build complete machine learning solutions—from data preparation and feature engineering to model training, APIs, cloud deployment, monitoring, and MLOps. One engineering team manages the entire ML lifecycle.

      ML Models
      Backend APIs
      Web Apps
      Mobile Apps
      SaaS Platforms
      ML APIs
      Cloud Deployment
      MLOps

      Production ML Development Process

      Every machine learning project follows a structured development process—from business discovery and data assessment to feature engineering, model training, validation, deployment, monitoring, and continuous model improvement as new data becomes available.

      Trusted by Machine Learning Clients

      From startups to global enterprises, Primocys builds secure, scalable machine learning solutions that power automation, predictions, and real-world business growth.

      ecofon communication - Primocys Emoji Tale - Primocys Only Singles -Primocys Orbis Elite -Primocys ZIBA Driver -Primocys MatchMums -Primocys apek electronic restoration -Primocys BURPOUT - Primocys WasaaChat - Primocys Prendi iL - Primocys Chat App - Primocys Batpay - Primocys Earnify - Primocys ZIO Gram - Primocys PROHUNTER - Primocys Lika Real Estate - Primocys ZIO Gram - Primocys ecofon communication - Primocys Emoji Tale - Primocys Only Singles -Primocys Orbis Elite -Primocys ZIBA Driver -Primocys MatchMums -Primocys apek electronic restoration -Primocys BURPOUT - Primocys WasaaChat - Primocys Prendi iL - Primocys Chat App - Primocys Batpay - Primocys Earnify - Primocys ZIO Gram - Primocys PROHUNTER - Primocys Lika Real Estate - Primocys ZIO Gram - Primocys
      1200+
      Platforms, Products, and Enterprise Systems Delivered
      150+
      Industry Recognitions and Technology Excellence Awards
      650+
      Enterprises and High-Growth Companies Served Globally
      8+
      Years Building Enterprise-Grade Systems
      50+
      Cross-Functional Experts in AI, Cloud & Platform Engineering
      MACHINE LEARNING DEVELOPMENT SERVICES

      Custom ML Services We Provide

      These are the commercial engagements clients can hire Primocys for. Each may use several of the core ML capabilities above, but the final solution is scoped around the data available, prediction target, product workflow and production requirements.

      01

      Custom Machine Learning Development

      End-to-end ML systems designed around a specific prediction, classification, ranking or optimization problem.

      • Problem & Target Definition
      • Data Pipeline Design
      • Model Architecture Selection
      • End-to-End System Build

      02

      Predictive Analytics Solutions

      Models that estimate future outcomes or probabilities from historical and current business signals.

      • Historical Data Modeling
      • Probability & Risk Scoring
      • Business Signal Integration
      • Continuous Model Updates

      03

      Recommendation Systems

      Personalized product, content, and item ranking using behavioral, contextual, and catalog signals to improve user engagement and conversion.

      • Behavioral Signal Modeling
      • Content & Catalog Ranking
      • Personalization Engines
      • Real-Time Recommendation Serving

      04

      Forecasting Systems

      Time-series and demand forecasting for planning, inventory, capacity, sales trends, resource allocation, and smarter operational decisions.

      • Time-Series Modeling
      • Demand & Inventory Forecasting
      • Capacity Planning Models
      • Seasonality & Trend Analysis

      05

      Classification & Anomaly Detection

      Systems for categorization, scoring, prioritization and unusual-pattern detection with threshold and review workflows.

      • Categorization & Scoring Models
      • Anomaly & Fraud Detection
      • Threshold Tuning
      • Human Review Workflows

      06

      Existing Model Improvement & MLOps

      Review, stabilize and productionize existing ML models with better pipelines, evaluation, serving, monitoring and retraining practices.

      • Model & Pipeline Audits
      • Serving & Monitoring Setup
      • Evaluation Framework Upgrades
      • Retraining & MLOps Automation
      Case Studies

      AI in Action: Real Products, Real Results

      Every product below was designed, built and is operated by our own team — not a proof-of-concept slide deck. See how our AI engineering holds up in live, everyday use.

      B2B SaaS · Customer Communication · AI Workflows

      ChatLivo

      The Challenge

      Companies were stuck choosing between costly enterprise chat suites with weak AI, or bare-bones free widgets that offered none at all. On top of that, conversations were scattered across the website and multiple channel plugins, leaving five disconnected inboxes with no shared history. None of these tools could actually understand what a customer was asking — they simply routed it to a human.

      The Solution

      We merged five separate channels into one unified inbox. The integrated AI assistant learns directly from the business’s own website content and custom FAQs, keeping every reply anchored to what the company actually communicates — available across both web and mobile so nothing gets missed.

      The Impact

      • 50+ businesses onboarded in the first month alone
      • Five scattered channels brought together in a single inbox
      • AI replies grounded in each business’s own material, not a canned script
      View Case Study arrow
      AI - ChatLivo UI design
      Consumer App · AI Storytelling · Mobile

      EmoTales

      The Challenge

      Parents were looking for a bedtime story made just for their child, not another recycled template repeated night after night — but coming up with something original after a long day isn’t easy. Add apps that only work in one language, and most families still couldn’t find stories that felt truly personal.

      The Solution

      EmoTales works on a simple idea: a child picks a few emojis, and AI turns that choice into a fully illustrated bedtime story in under a minute, complete with narration in the family’s preferred language and a selection of AI voices — including English, Hindi, Spanish and more.

      The Impact

      • More than 50,000 kids worldwide have created their own stories
      • A complete story generated from emojis in roughly 60 seconds
      • Multilingual storytelling backed by AI narration
      • A choice of AI voices for a more personal bedtime experience
      • Available on both iOS and Android
      View Case Study arrow
      AI - EmoTales app screens
      Fitness App Development · Mobile App · Health & Wellness

      Burpout

      The Challenge

      Most fitness apps push the same one-size-fits-all workout on every user, ignoring fitness level, personal goals or the equipment they actually have. A plan that doesn’t fit the person quickly kills motivation, and genuinely adaptive coaching remained locked behind expensive personal trainers.

      The Solution

      Burpout is powered by an AI coaching engine that builds a fully customized workout in under 30 seconds, based on the user’s goals, fitness level and available equipment. It works across both iOS and Android, so training isn’t limited to one device.

      The Impact

      • 25,000+ workouts logged by users so far
      • Custom plans generated in roughly 30 seconds
      • An adaptive AI coach instead of a fixed template
      • Works on both iOS and Android
      Case Study arrow
      AI - Burpout fitness app UI
      Real Estate App · Mobile App · Property Listing Platform

      Lika

      The Challenge

      Property platforms carrying large catalogs often grind to a halt as listings grow — heavy images, slow search, sluggish mobile performance — pushing away serious buyers before they ever book a viewing. Lika needed to scale beyond 100K listings without running into any of that slowdown.

      The Solution

      We built a real estate app engineered for scale: optimized image handling, fast search and filtering, and a lightweight mobile experience that keeps listings loading in under 3 seconds even with a catalog of 100K+ properties.

      The Impact

      • 100K+ property listings live on the platform
      • 96+ score on Mobile PageSpeed
      • Listings load in under 3 seconds
      • 3.2× improvement in lead-to-tour conversion
      View Case Study arrow
      AI - Lika real estate app UI
      Social Media App · Live Streaming · Flutter App

      Dapke

      The Challenge

      Creators wanted a live-streaming platform where going live actually translated into earnings, not just view counts. Most social apps add live video as an afterthought with no real monetization behind it, and real-time interaction between creators often lags too much to feel genuinely live.

      The Solution

      Dapke is a high-performance social app delivering sub-2-second live streaming latency, head-to-head PK battles between creators, and virtual gifts that convert directly into real earnings — running cross-platform on both iOS and Android.

      The Impact

      • 50,000+ active creators and viewers on the platform
      • Sub-2-second live streaming latency
      • 3× higher engagement than the industry average
      • Works on both iOS and Android
      View Case Study arrow
      AI - Dapke app UI screens
      Community App · Messaging & Live Streaming · Mobile

      Custom Islamic Community Chat App

      The Challenge

      This was an already-established community messaging app, not a ground-up build — it had to grow further without disturbing what existing members relied on. Admins wanted finer control over prayer and Masjid timings, members needed announcements and reminders that stayed reliable offline or after a restart, and live Azaan needed to keep playing even once the app moved to the background.

      The Solution

      We enhanced the Ummah and Ibadah Group modules with more detailed prayer, timing and admin controls, introduced MediaSoup to power live Azaan, live streaming and audio/video calling with background audio support, and added Apple Pay donations along with iOS subscription logic tied to actual plan permissions — while also fixing the state and navigation bugs that made chat, groups and reminders feel unreliable across sessions.

      The Impact

      • Multi-admin messaging permissions fixed
      • Live Azaan streaming powered by MediaSoup
      • Per-prayer reminders now fully configurable
      • Apple Pay donations and subscription limits introduced
      • Works on both iOS and Android
      View Case Study arrow
      Rabtah Islamic community chat app screens — groups, Dua Assistant, live Azaan
      Finance App · Income Tracking · iPhone App

      Earnify

      The Challenge

      Creators, freelancers, online sellers and independent professionals usually earn from several sources at once, yet have no straightforward way to track that income, work out taxes, or view the complete picture in one place. Existing finance apps felt far too complicated for something as routine as personal income tracking.

      The Solution

      Earnify is an iPhone app centered on managing income from multiple sources: analytics dashboards, recurring income tracking, tax planning, premium subscriptions and CSV/PDF exports, all packaged into a straightforward personal-finance workflow.

      The Impact

      • Every source of income tracked within a single app
      • Visual dashboards covering earnings, trends and analytics
      • Built-in tax planning alongside recurring income management
      • Premium subscriptions offering advanced export options
      View Case Study arrow
      Earnify iPhone income tracking app UI screens
      What We Build

      Machine Learning Systems We Build

      The same ML techniques can support very different products. We define where a prediction enters the workflow, how users act on it and what happens when confidence is low before deciding the model architecture.

      01

      Recommendation Engines

      Personalized ranking for commerce, media, marketplaces and SaaS products.

      02

      Demand & Revenue Forecasting

      Forecasting pipelines for planning decisions where historical data and seasonality are meaningful.

      03

      Churn & Propensity Models

      Risk or likelihood scoring that helps teams prioritize retention, sales or engagement workflows.

      04

      Fraud & Anomaly Signals

      Models that surface unusual behavior for investigation rather than silently making high-impact decisions.

      05

      Intelligent Search & Ranking

      Learned relevance and ranking components for catalogs, listings, content and internal information systems.

      06

      ML Features Inside Existing Apps

      Add predictions, recommendations or classification to an existing SaaS, web platform or mobile application.

      Business Value

      Where Machine Learning Creates Practical Business Value

      Machine learning is useful when historical or behavioral data contains patterns that can improve a repeatable decision. We focus on measurable tasks such as ranking, forecasting, classification and anomaly detection rather than adding ML where deterministic software would be simpler.

      Predict What Happens Next

      Use historical signals to support demand, risk, churn, lead or operational forecasts where the data is suitable.

      Rank Better Options

      Prioritize products, content, leads or actions using learned relevance signals instead of fixed ordering alone.

      Detect Unusual Patterns

      Surface abnormal behavior, transactions, system patterns or operational events for review.

      Automate Repeated Decisions

      Classify or score high-volume inputs consistently while routing uncertain or high-impact cases to people.

      Why Primocys

      Why Choose Our Machine Learning Development Services

      Our machine learning development services help businesses automate decisions, uncover valuable insights, improve predictions, and deploy secure, scalable ML solutions for real-world products.

      Machine Learning Development Services

      Secure Machine Learning Solutions

      • Protect sensitive business data with secure ML pipelines, encryption, and enterprise-grade access controls.
      • Build machine learning systems that align with governance, compliance, and long-term security requirements.

      Intelligent Business Automation

      • Automate repetitive workflows using predictive models, anomaly detection, and intelligent decision-making.
      • Reduce manual effort while improving operational efficiency with real-time ML-powered automation.

      Predictive Analytics & Insights

      • Turn business data into actionable insights through forecasting, customer behavior analysis, and recommendation systems.
      • Support smarter decisions with machine learning models built around measurable business outcomes.

      Scalable ML Deployment & Monitoring

      • Deploy ML models on cloud infrastructure with APIs, versioning, and production-ready serving.
      • Monitor model performance, detect data drift, and keep ML systems reliable as your business grows.
      Client Testimonials

      What our clients Say
      About Us

      Our Client
      Reviews

      Adegbuyi Oduguwa Gregor Skerl Revanth K Dorian Çoçka

      Customer experiences that speak for themselves

      Contact Us arrow
      Adegbuyi Oduguwa
      Adegbuyi Oduguwa
      CEO & Founder

      Our B2B and B2C platform helps Nigerian manufacturers sell at wholesale prices and suppliers offer competitive retail pricing, with a strong focus on Made in Africa products and easy local and international distribution. The app has received excellent user reviews for its design and unique features. Communication with the Primocys team was smooth in an agile setup, even beyond office hours when needed. Their mobile app development expertise is excellent—highly professional and reliable.

      Gregor Skerl
      Gregor Skerl
      Executive

      We hired Primocys to develop a highly complex and specialized mobile application, and they delivered outstanding results. The app includes advanced features such as timeline mixers, classifieds, payments, advertisements, GPS functionality, and more. Their technical skills, timely delivery, availability, and the personal attention Arpan Sagar brings to each project truly stand out. The team stays focused and committed from start to finish—an excellent experience overall.

      Revanth K
      Revanth K
      Founder PROHUNTER
      ”

      The dating app was delivered successfully and approved by both Apple App Store and Google Play. Our users are highly impressed with the design, UI, and overall functionality. The project was well planned with clear milestones, and all modules were delivered on time. The team is talented, patient, and flexible, accommodating multiple scope revisions as requirements evolved. Their 24/7 development and support availability made the entire process smooth and reliable.

      Dorian Çoçka
      Dorian Çoçka
      DRH Code

      Great team with excellent communication and a strong commitment to on-time delivery. They developed a fully customized mobile app for both Android and iOS, perfectly matching our requirements. The entire process was smooth and professional, with clear updates at every stage. They are reliable, skilled, and very easy to work with. We’re continuing our partnership on more projects, and choosing them has been one of the best business decisions I’ve made.

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      100% JOB SUCCESS
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      Machine Learning Technology Stack

      Tools Selected Around Your ML Requirements

      The stack depends on data volume, model family, training needs, latency, cloud environment and prediction consumption.

      ML & Data

      • Python
      • scikit-learn
      • XGBoost
      • LightGBM
      • Pandas
      • NumPy

      Deep Learning

      • PyTorch
      • TensorFlow
      • Hugging Face

      Experimentation & MLOps

      • MLflow
      • Weights & Biases
      • Docker
      • CI/CD
      • Model registries

      Serving & Product Integration

      • FastAPI
      • Node.js
      • PostgreSQL
      • Redis
      • REST APIs
      • Event pipelines

      Cloud

      • AWS
      • Azure
      • Google Cloud
      • Managed ML services where appropriate
      Process

      Our ML Development Process

      We follow a structured ML development process to build intelligent, scalable, and data-driven solutions tailored to your business needs.

      01
      Problem Definition
      Define target, user, workflow, constraints and success metric.
      02
      Data Assessment
      Review sources, labels, quality, volume, leakage and access constraints.
      03
      Baseline & Feasibility
      Establish a simple benchmark and test whether useful signal exists.
      04
      Model Development
      Engineer features, train candidates and track experiments reproducibly.
      05
      Evaluation
      Measure task metrics, segment behavior and business-relevant errors.
      06
      Product Integration
      Connect predictions to APIs, UI, workflows and downstream systems.
      07
      Deployment
      Version, release and monitor the model and serving infrastructure.
      08
      Monitor & Improve
      Review drift, outcomes, failures and retraining needs as new data arrives.
      Existing Model & Project Takeover

      Already Have a Notebook, Model or Partial ML Product?

      You do not need to restart automatically. We can review an existing data pipeline, training code, model artifact, API or production implementation and identify what should be retained, corrected or rebuilt.

      Model & Data Review

      Inspect preprocessing, leakage risks, labels, features, evaluation and reproducibility.

      Notebook to Production

      Turn experimental code into tested pipelines, versioned artifacts and deployable services.

      Performance Investigation

      Analyze errors, segments, drift and serving behavior before assuming retraining is the answer.

      ML Inside Existing Software

      Integrate an existing or improved model into your current SaaS, web, mobile or internal application.

      Our Expert Solutions

      Machine Learning Use Cases We Build

      Machine learning delivers the most value where data supports better decisions. These use cases show how predictive models, forecasting, and intelligent ranking improve products.

      AI Photo & Video Sharing App
      AI On-Demand Application
      AI Business Listing App
      AI Automotive App
      AI Real Estate App
      AI Education App
      AI Healthcare & Fitness App
      AI Ecommerce & Shopping App
      AI Banking & Finance App
      AI Food & Restaurant App
      AI Media & Social App
      AI Hotel Booking App
      AI Sports App

      Let’s make something great work together. – Get Free Quote

      Cost & Scope

      What Drives Machine Learning Development Cost?

      ML cost depends heavily on data readiness and production requirements. A focused model using clean historical data is a different project from building ingestion pipelines, labeling workflows, real-time serving, monitoring and application interfaces around a new ML capability.

      Data Readiness

      Availability, quality, labels, joins, historical coverage and the amount of preprocessing required.

      Problem Complexity

      Prediction type, number of targets, model families, explainability needs and evaluation requirements.

      Training Requirements

      Dataset size, compute needs, experiment volume and whether deep learning is actually necessary.

      Inference Pattern

      Offline batch predictions versus low-latency online inference, concurrency and availability needs.

      Product Integration

      APIs, dashboards, mobile/web interfaces, authentication and downstream workflows.

      MLOps & Monitoring

      Experiment tracking, model registry, drift monitoring, feedback loops and retraining automation.

      FAQ

      Frequently Asked Questions

      Our work reflects who we are. Each project is a testament to our expertise. Our work reflects who we are.

      What is machine learning development?
      Machine learning development is the process of designing software that learns patterns from data for tasks such as prediction, classification, ranking, forecasting or anomaly detection. A production project usually includes data preparation, model development, evaluation, serving and monitoring—not only training a model.

      What is the difference between AI development and machine learning development?
      Machine learning is one technical area within the broader AI field. This page focuses on predictive and learned models built from data. Broader AI development may also include LLM applications, RAG, AI agents, generative AI and other AI-powered product capabilities.

      How much data do we need for an ML project?
      There is no universal minimum. It depends on the task, feature quality, label quality, variability, model type and acceptable error. We assess the available data and establish a baseline before recommending a larger ML build.

      Do you always use deep learning?
      No. Classical ML can be faster, cheaper and easier to explain for many structured-data problems. We choose the simplest model family that meets the required quality and operational constraints.

      Can you improve an existing machine learning model?
      Yes. We can review data preparation, features, validation, leakage, model choice, errors, serving and monitoring before deciding whether the right solution is retraining, architecture changes or a better product workflow.

      Can you deploy an ML model into our existing software?
      Yes. Models can be exposed through APIs, batch pipelines or event-driven services and integrated into existing web, mobile, SaaS or internal applications depending on the required inference pattern.

      How do you evaluate machine learning models?
      Evaluation depends on the task. We define appropriate metrics, compare against a baseline, use a suitable holdout or cross-validation strategy and analyze errors across important segments. Production monitoring is then used to detect changes after deployment.

      What happens if model accuracy drops after launch?

      The correct response depends on the cause. Data drift, concept drift, pipeline changes, missing features or product behavior can all affect performance. Monitoring should help identify the change before retraining or model replacement is chosen.

      How long does machine learning development take?
      Timeline depends on data readiness, task complexity, experimentation, integrations and deployment requirements. We scope the timeline after reviewing the problem and available data rather than publishing one duration for every ML project.

      How much does machine learning development cost?
      Cost depends on data preparation, model complexity, compute, evaluation, product integration, serving and MLOps requirements. Primocys provides a scope-based estimate after technical discovery.

      Build Smarter Products
      With Machine Learning

      Turn your business data into intelligent products with custom ML development. From predictive analytics and recommendations to forecasting, anomaly detection and MLOps, we build secure, scalable ML solutions ready for production.

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