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AI Innovation Leaders

AI & Machine Learning Company in Stockholm

Stockholm is Europe's unicorn factory, producing more billion-dollar startups per capita than any city outside Silicon Valley. Home to Spotify, Klarna, King, and iZettle, the city has a unique culture of innovation that blends design thinking with engineering excellence. Our Stockholm team builds world-class products for the Nordic region's most ambitious tech companies.

65M+
Users on Our Apps
99%
Client Satisfaction
15+
Nordic Projects
9wk
Avg MVP Delivery

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Codazz — Top Generative AI Company on Clutch 2026
4.9/5
Clutch Rating
500+
Projects Delivered
ISO
27001 Certified
SOC II
Compliant
99%
Client Satisfaction
AWS Advanced Tier PartnerSOC II CompliantISO 27001 CertifiedWebby Award Honoree
Service Overview

AI & Machine Learning Solutions for Stockholm Businesses

Stockholm is the operating capital of Nordic AI shipping. Spotify (Stockholm HQ) defines global music recommendation, Discover Weekly, the annual Wrapped product, and the DJ AI feature that personalises listening for more than 600M monthly active users. Klarna runs production AI across BNPL credit decisioning, fraud detection, and customer service automation for 150M+ shoppers across 45 markets. Mojang Studios (Microsoft, Stockholm HQ) embeds ML into Minecraft content moderation and creator tooling. Truecaller (Stockholm HQ) operates one of the world's largest spam-call ML systems across 400M+ users. Detectify ships security AI. Codazz builds production AI and machine learning systems for Stockholm founders, fintechs, gaming studios, ad-tech platforms, and enterprises working at this standard. We deliver RAG assistants, recommendation models, fraud and credit decisioning, computer vision, and LLM integrations that comply with the EU AI Act risk classification regime applicable from August 2024 with prohibitions live since February 2025 and high-risk obligations applying through 2026 and 2027, GDPR enforced by the Integritetsskyddsmyndigheten (IMY) in Sweden, the Swedish Data Protection Act (SFS 2018:218), Swedish Financial Supervisory Authority (Finansinspektionen) expectations for regulated AI, Spelinspektionen rules for gambling-adjacent AI, and the European Accessibility Act applying from June 28 2025. Our engineers work CET hours from our Chandigarh and Berlin-adjacent hubs, deliver model cards, bias audits, and EU AI Act Conformity Assessment artefacts suitable for IMY and Finansinspektionen review, and use AWS eu-north-1 (Stockholm region, one of the lowest-carbon AWS regions globally thanks to Nordic hydro and wind power), Azure Sweden Central (Gavle), and GCP europe-north1 (Hamina, Finland) for low-carbon training and inference. Instead of decks, you get a working model, an MLOps pipeline, and a compliance trail your DPO and risk committee can defend in front of IMY and FI.

Stockholm is Europe's unicorn factory, producing more billion-dollar startups per capita than any city outside Silicon Valley. Home to Spotify, Klarna, King, and iZettle, the city has a unique culture of innovation that blends design thinking with engineering excellence. Our Stockholm team builds world-class products for the Nordic region's most ambitious tech companies.

Why AI & Machine Learning in Stockholm?

Stockholm, Stockholm is a thriving hub for technology and innovation. Businesses here demand top-tier ai & machine learning solutions that can compete on a global stage while addressing local market needs. Our team combines deep technical expertise with an understanding of Stockholm's unique business landscape to deliver solutions that drive measurable results.

8+
Years Experience
24
Countries Served
200+
Engineers

What You Get

Custom-built solutions tailored to your business
Dedicated project manager in your timezone
Agile development with weekly sprint demos
Full source code ownership from day one
Comprehensive QA and security testing
90-day post-launch support included
NDA and IP protection guaranteed
Fixed-price or flexible engagement models
What We Build

AI & Machine Learning Services We Offer in Stockholm

Stockholm AI buyers have Spotify, Klarna, and Truecaller as their internal reference. Our AI and ML services match that benchmark. We design retrieval pipelines on Anthropic, OpenAI, Mistral, and Cohere APIs with EU data residency in eu-north-1 or eu-west-1, fine-tune open-weight models (Llama 3.3, Mistral, Qwen, Mixtral) on client data when EU AI Act transparency obligations or Swedish public sector procurement rule out US-hosted frontier models, and build classical ML (XGBoost, LightGBM, scikit-learn) for tabular fintech, ad-tech, and gaming problems where explainability beats raw accuracy. Recommendation systems use two-tower retrieval and learning-to-rank patterns proven inside Spotify and iZettle-era PayPal. Every engagement ships with a model card, a bias review including representation across Swedish, Sami, and migrant population segments where relevant, and an EU AI Act risk classification with Article 6 high-risk Conformity Assessment artefacts where the system meets the threshold.

01
🤖

LLM Integration & AI Automation

Integrate large language models like GPT-4, Claude, and Gemini into your products and workflows. We build custom AI agents, RAG pipelines, intelligent document processing systems, and automated content generation tools that save hundreds of hours per month.

OpenAIClaude APILangChainRAGAI Agents
02
👁️

Computer Vision & Predictive Analytics

Deploy custom machine learning models for image recognition, object detection, anomaly detection, and predictive forecasting. From quality control in manufacturing to demand prediction in retail, we build models that deliver measurable ROI.

TensorFlowPyTorchYOLOScikit-learnMLOps
💬

AI Chatbots & Virtual Assistants

Build intelligent conversational AI that handles customer inquiries, books appointments, and provides 24/7 support with human-like responses.

📈

Predictive Analytics & Forecasting

Leverage historical data to forecast demand, detect churn, optimize pricing, and make data-driven decisions with custom ML models.

📄

Intelligent Document Processing

Automate data extraction from invoices, contracts, and forms using OCR and NLP to eliminate manual data entry and reduce errors.

🔗

AI Strategy & Consulting

Identify high-impact AI opportunities in your business with a comprehensive audit, feasibility analysis, and implementation roadmap.

Industry Expertise

AI & Machine Learning for Stockholm's Key Industries

Stockholm AI demand concentrates across four verticals, and we have shipped in all of them. In financial services and fintech, Klarna, SEB, Swedbank, Handelsbanken, Nordea Sweden, and Avanza invest in fraud detection, AML transaction monitoring under the EU Sixth AML Directive and Swedish Penningtvattslagen, credit decisioning under Konsumentkreditlagen, and document intelligence. We build these under Finansinspektionen outsourcing expectations and EBA Guidelines on ICT and security risk management. In music, audio, and ad-tech, Spotify, Storytel, Cint, and Acast set the bar on recommendation, ranking, and audience modelling. Our pipelines deliver retrieval, ranking, and uplift modelling under GDPR Article 22 automated decision-making constraints. In gaming, Mojang Studios, Paradox Interactive, Embark Studios, and King (Stockholm presence) drive content moderation, anti-cheat, and player matchmaking ML. In communications and security, Truecaller, Detectify, and Sinch run spam-call ML, vulnerability detection, and fraud-call classification at planetary scale.

💳
FintechAI & Machine Learning Solutions
🎮
GamingAI & Machine Learning Solutions
🎯
Music TechAI & Machine Learning Solutions
🛒
E-CommerceAI & Machine Learning Solutions
☁️
SaaSAI & Machine Learning Solutions
Our Process

Our AI & Machine Learning Development Process

We run discovery, design, build, and deployment on CET hours so Stockholm product, DPO, and risk leads get synchronous standups, not next-day handoffs. Discovery opens with an EU AI Act risk classification (prohibited, high-risk, limited-risk transparency, minimal-risk) and a GDPR Article 35 DPIA where automated decision-making affects individuals. Finansinspektionen-regulated clients get an operational resilience and outsourcing risk register before any model touches production data. Spelinspektionen-touching gambling or skill-game work gets a separate AML and responsible-gaming model review. Build sprints are two weeks, reviewed against a model card template aligned with EU AI Act Article 13 transparency and Article 14 human oversight obligations. Deployment includes monitoring, drift detection, post-market monitoring under EU AI Act Article 72 where applicable, and a documented rollback plan that IMY complaints, FI thematic reviews, and your internal audit can satisfy without a second vendor engagement.

01

AI Opportunity Assessment

1-2 Weeks

We audit your data, workflows, and business goals to identify the highest-impact AI use cases and evaluate technical feasibility.

Deliverables
AI Opportunity ReportData Readiness AssessmentFeasibility AnalysisROI Projections
02

Data Engineering & Preparation

2-4 Weeks

We clean, label, and structure your data for model training. This includes building data pipelines, feature engineering, and establishing data quality benchmarks.

Deliverables
Data Pipeline ArchitectureCleaned & Labeled DatasetsFeature Engineering ReportData Quality Metrics
03

Model Development & Training

4-8 Weeks

Our ML engineers build, train, and fine-tune models using state-of-the-art techniques. We run experiments, optimize hyperparameters, and validate results.

Deliverables
Trained ML ModelsExperiment Tracking ReportsModel Performance MetricsComparison Benchmarks
04

Integration & Testing

2-4 Weeks

We integrate the AI model into your existing systems via APIs, build monitoring dashboards, and conduct thorough testing with real-world data.

Deliverables
API EndpointsIntegration DocumentationA/B Test ResultsMonitoring Dashboard
05

Deployment & MLOps

1-2 Weeks

Production deployment with automated retraining pipelines, model versioning, drift detection, and performance monitoring for continuous improvement.

Deliverables
Production DeploymentMLOps PipelineModel Monitoring AlertsRetraining Schedule
Technology

Technologies We Use for AI & Machine Learning

We default to AWS eu-north-1 (Stockholm region, one of the lowest-carbon AWS regions globally on Nordic hydro and wind) for training and inference, Azure Sweden Central (Gavle, opened 2021) where Microsoft-aligned clients specify it, and GCP europe-north1 (Hamina, Finland, seawater-cooled) where Google standards apply. For LLM layers we use Anthropic and OpenAI through Bedrock or Azure in eu-north-1 and eu-west-1 with explicit no-train data processing terms, Mistral La Plateforme for EU-sovereign frontier inference, and self-hosted Llama 3.3 or Mistral on GPU instances when EU AI Act explainability obligations or Swedish public sector procurement rule out closed APIs entirely. MLflow, Weights and Biases, and SageMaker handle experiment tracking. SHAP, LIME, and Captum produce the explainability artefacts that EU AI Act Article 13 transparency, IMY, and FI expect for higher-risk models.

LLM & NLP
OpenAI GPT-4Claude APILangChainHugging FacespaCy
LLM & NLP
OpenAI GPT-4 · Claude API · LangChain · Hugging Face +1 more
ML Frameworks
TensorFlow · PyTorch · Scikit-learn · XGBoost +1 more
Data & MLOps
Python · Pandas · MLflow · Weights & Biases +1 more
Cloud AI Services
AWS SageMaker · Google Vertex AI · Azure ML · Pinecone +1 more
Why Choose Us

Why Stockholm Businesses Choose Codazz for AI & Machine Learning

We combine world-class engineering with local market understanding to deliver ai & machine learning solutions that drive real business outcomes.

🎵

Spotify & Klarna Recommendation DNA

Stockholm's AI talent has shipped recommendation, fraud, and credit ML at hundreds of millions of users through Spotify, Klarna, and Truecaller. We benchmark our retrieval, ranking, and uplift modelling against that bar, not against off-the-shelf vendor demos that fall over at production scale.

🇪🇺

EU AI Act & GDPR Native

Every model ships with an EU AI Act risk classification, an Article 35 GDPR DPIA where applicable, Article 13 transparency artefacts, and Article 14 human oversight controls. IMY enforcement and Finansinspektionen outsourcing reviews are designed into the build, not retrofitted under a regulator's enforcement letter.

🌿

Lowest-Carbon AWS Region

AWS eu-north-1 (Stockholm) runs on Nordic hydro and wind power, making it one of the lowest-carbon AWS regions globally. We deliver Scope 3 per-training-run carbon figures aligned with CSRD ESRS E1 and SBTi, and we batch training to high-renewable grid hours where the workload permits.

🏦

FI & EBA Outsourcing Experience

SEB, Swedbank, Handelsbanken, Nordea Sweden, and Klarna set the bar on regulated AI inside Finansinspektionen and EBA Guidelines on ICT and security risk management. We ship model risk documentation, challenger testing, and operational resilience artefacts that FI and internal audit accept on first review.

📍

Local Expertise

Our team understands the regulatory landscape, business culture, and user expectations specific to your city. We combine global engineering standards with hyper-local market knowledge to build products that resonate with your target audience from day one.

📈

Proven Track Record

With 500+ projects delivered across 24 countries since 2018, we bring battle-tested processes and domain expertise to every engagement. Our client retention rate of 94% speaks to the long-term partnerships we build, not just one-off projects.

👥

Dedicated Team

Every project gets a dedicated cross-functional team including a project manager, lead architect, senior developers, QA engineers, and a DevOps specialist. No freelancers, no outsourcing your project to third parties - your team is your team throughout.

🛠️

Post-Launch Support

Our relationship does not end at deployment. We provide 90 days of complimentary post-launch support, proactive monitoring, performance optimization, and a dedicated Slack channel for your team. Most clients continue with our maintenance retainer plans.

Featured Results

Real Results from Real Projects

We measure success by the impact we create. Here are three recent projects that showcase our ai & machine learning capabilities.

💳
FinTech

Digital Banking Platform

Built a full-stack digital banking app with real-time payments, biometric auth, and PCI-DSS compliance. Scaled from 0 to 100K+ active users within 8 months of launch.

4.9★
App Store Rating
100K+
Active Users
99.99%
Uptime SLA
React NativeNode.jsAWSStripe
🛒
E-Commerce

Omnichannel Retail Platform

Designed and developed a headless commerce platform integrating 12 sales channels with unified inventory, AI-powered recommendations, and sub-second page loads globally.

3x
Revenue Growth
340%
Conversion Lift
<0.8s
Load Time
Next.jsShopify PlusAlgoliaVercel
🏥
Healthcare

Telehealth & Patient Portal

Delivered a HIPAA-compliant telehealth platform with video consultations, EHR integration, e-prescriptions, and a patient portal serving 50K+ patients across 200+ providers.

HIPAA
Compliant
50K+
Patients Served
4.8★
Provider Rating
ReactPythonFHIRAzure
Client Testimonials

What Stockholm Clients Say About Us

Real feedback from businesses we have partnered with on ai & machine learning projects.

Payment platform processing SEK 5B monthly across the Nordics. PSD2 compliant with 99.99% uptime — our merchants and regulators are equally satisfied.

E
Erik Johansson
CTO, NordPay Solutions

Audio streaming platform with 2M+ subscribers. Codazz built recommendation algorithms that increased listening time by 35% — users are more engaged than ever.

L
Linnea Andersson
VP Product, SoundWave Studios

Multiplayer game backend handling 500K concurrent players. Zero downtime during peak launches — a first for us after years of launch-day crashes.

M
Magnus Lindqvist
Head of Engineering, Viking Games AB
FAQs

Frequently Asked Questions About AI & Machine Learning in Stockholm

Have a question not listed here? Reach out to our team and we will get back to you within 4 hours.

Ask a Question

A scoped AI proof of concept at Stockholm rates runs SEK 380,000 to 900,000 (roughly EUR 33,000 to 80,000 or USD 36,000 to 86,000 at recent spot rates) over six to ten weeks, covering data audit, baseline model, and hosted demo. A custom production ML model (fraud scoring, credit decisioning, recommendation, document extraction) typically lands at SEK 1.1M to 2.8M (EUR 95,000 to 245,000). Full production AI systems with RAG, multiple models, fine-tuning, and enterprise integrations range from SEK 2.6M to 11M (EUR 230,000 to 970,000). Stockholm sits at the top of Nordic AI rates because of the Spotify, Klarna, and Truecaller talent premium, though typically below London on full-stack ML pricing. We give fixed-fee proposals rather than open T and M estimates.

The EU AI Act applies in stages: prohibitions on unacceptable risk systems live since 2 February 2025, general-purpose AI obligations from 2 August 2025, high-risk system obligations from 2 August 2026, and additional high-risk obligations through 2 August 2027. Our discovery phase classifies your system across the four risk tiers, runs an Article 35 GDPR DPIA where automated decision-making is in scope, and produces a Conformity Assessment plan for high-risk systems (Annex III categories including credit scoring, employment screening, education access, essential services, law enforcement, migration). High-risk builds ship with technical documentation under Article 11, a quality management system under Article 17, human oversight controls under Article 14, accuracy and robustness testing under Article 15, and post-market monitoring under Article 72. IMY enforces in Sweden alongside Finansinspektionen where finance touches AI.

Yes. We ship RAG systems, internal copilots, document extraction pipelines, and agent workflows for Nordic banks and fintechs. For SEB, Swedbank, Handelsbanken, Nordea Sweden, Klarna, and Avanza we stay inside EU regions (Bedrock and Azure OpenAI in eu-north-1 and eu-west-1, Mistral La Plateforme for EU-sovereign inference), apply Finansinspektionen outsourcing requirements and EBA Guidelines on ICT risk, and produce the model risk documentation internal audit needs. We have patterned deployments after public work from Klarna AI Assistant (the OpenAI-powered customer service rollout) and the AML transaction monitoring patterns Nordic banks share through the Nordic Financial CERT and EBA Q&A. Output logs feed existing SIEM and model risk platforms.

GDPR Article 22 restricts solely automated decisions producing legal or similarly significant effects, with carve-outs for contract necessity, explicit consent, or EU/Swedish law authorisation. Our discovery phase identifies any Article 22 trigger (credit decisioning under Konsumentkreditlagen, employment screening, insurance underwriting, essential service access) and designs in human review, the right to obtain human intervention, and meaningful information about the logic under Articles 13(2)(f) and 15(1)(h). For Klarna-style consumer credit we follow the Swedish Konsumentverket guidance, the EU Consumer Credit Directive 2023 obligations applying through 2026, and IMY's published views on profiling. Outputs include a Schrems II transfer impact assessment where US sub-processors are involved.

We default to AWS eu-north-1 (Stockholm region, lowest-carbon AWS region globally on Nordic hydro and wind power) for training and inference, with eu-west-1 (Dublin) as the cross-region replication and DR target. Azure Sweden Central (Gavle, opened 2021) supports Microsoft-aligned clients, and GCP europe-north1 (Hamina, Finland, seawater-cooled) covers Google standards. For LLMs that must stay in the EU we use Mistral La Plateforme, Bedrock with no-train Anthropic and Cohere terms, and self-hosted Llama 3.3 or Mistral on EU GPU instances. Cross-border to US regions is governed by an explicit Schrems II Transfer Impact Assessment under EDPB guidance, with the EU-US Data Privacy Framework as the standard transfer mechanism for certified US recipients.

A typical Stockholm fintech model (fraud scoring, AML transaction monitoring, credit decisioning, KYC document extraction) takes fourteen to twenty-four weeks from kickoff to production, assuming clean historical data and Finansinspektionen outsourcing documentation as part of scope. Week 1 to 4 is data audit, DPIA, and EU AI Act classification baseline. Week 5 to 12 is modelling, iteration, and challenger testing. Week 13 to 18 is MLOps, monitoring, shadow mode deployment, and internal audit review. Week 19 onward is gradual rollout under FI conduct expectations. If you are pre-data or need labelling, add six to eight weeks. We have shipped to this cadence inside FI-supervised stacks alongside Klarna-style BNPL and SEB-style traditional banking architectures.

Yes, and it is one of the strongest reasons to host AI workloads in Stockholm. AWS eu-north-1 is one of the lowest-carbon AWS regions globally, running on Swedish grid power dominated by hydro and wind. Azure Sweden Central (Gavle) and GCP europe-north1 (Hamina, Finland) operate on similarly clean Nordic energy. For clients with CSRD sustainability reporting obligations or Science Based Targets initiative commitments, we deliver a Scope 3 carbon estimate per training run using the AWS Customer Carbon Footprint Tool, Microsoft Sustainability Manager, or Google Cloud Carbon Footprint, and design batch training to coincide with high-renewable hours on the Swedish grid. CSRD ESRS E1 climate disclosures get specific compute-emissions numbers, not a hand-waved estimate.

Yes, and we design for it on day one. Spotify, Klarna, Truecaller, and Storytel serve hundreds of millions of users across the EU, US, UK, Latin America, India, and Southeast Asia, which means EU AI Act, GDPR, US state laws (Colorado AI Act, California SB-1047 follow-ons, NYC Local Law 144), UK ICO, India DPDP Act 2023, and Brazil LGPD obligations stack. We architect models with regional data isolation, route EU customer inference through eu-north-1, route US through us-east-1 or us-west-2, and keep UK customers inside eu-west-2 (London) under the UK Adequacy Decision. EU AI Act risk classification ships in the model card from the start so a future Conformity Assessment is not a rewrite.

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Other Services We Offer in Stockholm

Looking for a different service? Explore our full range of technology solutions available in Stockholm.

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Design in Stockholm
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LLM IntegrationAI AutomationComputer VisionPredictive AnalyticsAI Chatbot Development

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Stockholm is the operating capital of Nordic AI shipping. Spotify (Stockholm HQ) defines global music recommendation, Discover Weekly, the annual Wrapped product, and the DJ AI feature that personalises listening for more than 600M monthly active users. Klarna runs production AI across BNPL credit decisioning, fraud detection, and customer service automation for 150M+ shoppers across 45 markets. Mojang Studios (Microsoft, Stockholm HQ) embeds ML into Minecraft content moderation and creator tooling. Truecaller (Stockholm HQ) operates one of the world's largest spam-call ML systems across 400M+ users. Detectify ships security AI. Codazz builds production AI and machine learning systems for Stockholm founders, fintechs, gaming studios, ad-tech platforms, and enterprises working at this standard. We deliver RAG assistants, recommendation models, fraud and credit decisioning, computer vision, and LLM integrations that comply with the EU AI Act risk classification regime applicable from August 2024 with prohibitions live since February 2025 and high-risk obligations applying through 2026 and 2027, GDPR enforced by the Integritetsskyddsmyndigheten (IMY) in Sweden, the Swedish Data Protection Act (SFS 2018:218), Swedish Financial Supervisory Authority (Finansinspektionen) expectations for regulated AI, Spelinspektionen rules for gambling-adjacent AI, and the European Accessibility Act applying from June 28 2025. Our engineers work CET hours from our Chandigarh and Berlin-adjacent hubs, deliver model cards, bias audits, and EU AI Act Conformity Assessment artefacts suitable for IMY and Finansinspektionen review, and use AWS eu-north-1 (Stockholm region, one of the lowest-carbon AWS regions globally thanks to Nordic hydro and wind power), Azure Sweden Central (Gavle), and GCP europe-north1 (Hamina, Finland) for low-carbon training and inference. Instead of decks, you get a working model, an MLOps pipeline, and a compliance trail your DPO and risk committee can defend in front of IMY and FI.

NDA on Day 1
Fixed-Price Guarantee
48hr Proposal
Secure Data Residency
Average response time: 4 hours
Selected Projects

Latest Work

📱 Mobile Apps🌐 Web Platforms🤖 AI Products💰 FinTech🏥 HealthTech🛒 E-Commerce📚 EdTech🚚 Logistics🏠 Real Estate🎮 Gaming
📱 Mobile Apps🌐 Web Platforms🤖 AI Products💰 FinTech🏥 HealthTech🛒 E-Commerce📚 EdTech🚚 Logistics🏠 Real Estate🎮 Gaming
Web Design3D Animation
01

Rapida

Delivery Service Platform

A high-performance delivery platform with real-time tracking and immersive 3D visualizations.

UI/UXSecurity
02

Fynsec

Cybersecurity Dashboard

Enterprise-grade security dashboard with real-time threat monitoring and analytics.

E-CommerceCreative
03

Pallet Ross

Art Marketplace

A curated marketplace connecting artists with collectors worldwide.

Mobile DevFlutter
04

Rapida Mobile

iOS/Android App

Cross-platform mobile experience with seamless delivery tracking and notifications.

APIMicroservices
05

Fynsec API

Backend Infrastructure

Scalable microservices architecture handling millions of security events daily.

Admin PanelAnalytics
06

Pallet Ross Admin

CMS Dashboard

Comprehensive content management system with advanced analytics and reporting.

01 / 06

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Our Work

Products That Users Actually Love.

200+ products shipped across fintech, healthcare, e-commerce, and SaaS — built to scale, designed to convert.

Mobile App

FinTech Trading Platform

FinTech Startup

Results
2.1B+ Transactions
50ms Latency
4.8★ Rating
Technology
React NativeNode.jsAWS
Healthcare App

Telehealth Solution

Healthcare Network

Results
120+ Clinics
500K Consultations
HIPAA Certified
Technology
SwiftKotlinGCP
Mobile Platform

E-Commerce Marketplace

E-Commerce Brand

Results
85K MAU
28% Conversion
$12M GMV
Technology
FlutterGoMongoDB