Miquido
Polish ML development house known for rapid GenAI delivery and mobile-embedded ML applications
Founded 2011 | Kraków, Poland | 200+ employees
custom-mlgenerative-ainlpcomputer-visionmlops
What is Miquido?
Miquido is a product and technology company founded in 2011 and headquartered in Kraków, Poland, with 200+ employees. The firm offers custom machine learning development alongside mobile and product engineering, making it a strong option when ML needs to be embedded within a mobile or SaaS product. Miquido is recognised for rapid generative AI delivery — offering GenAI app demos in two days and full products in four weeks — and has delivered for clients in finance, media, and healthcare.
Miquido was founded in 2011 and is headquartered in Kraków, Poland. The firm employs 200+ people and works primarily with clients in Financial Services, Media & Entertainment, Healthcare & Life Sciences, Retail & E-commerce, SaaS & Technology sectors. Its primary differentiator is: GenAI and mobile ML integration in one team — a rare combination for companies building AI-native products for end users.
Miquido tech stack and services
TensorFlowPyTorchOpenAIHugging FaceAWSGCPTensorFlow LiteCore ML
| Service area |
|---|
| Custom ML Development |
| Generative AI |
| NLP & LLMs |
| Computer Vision |
| MLOps & Deployment |
Miquido use cases
Short answer: Miquido is best suited for product companies, ML/GenAI embedded, fast time-to-demo.
| Use case |
|---|
| AI-native mobile application with on-device ML inference for fintech |
| GenAI content creation and moderation features embedded in a media SaaS platform |
| Computer vision feature integrated into a consumer healthcare mobile app |
| LLM-powered chatbot built into an existing e-commerce product in four weeks |
| Personalisation ML layer added to a SaaS analytics product |
Miquido pricing
Short answer: Miquido uses a fixed project, t&m pricing approach. Minimum engagement starts at $30K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $30K | Well-defined scope |
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
Miquido does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Miquido pros and cons
| Advantages | Things to consider |
|---|---|
| +Fastest GenAI prototyping in the market — demo in 2 days, full product in 4 weeks claim (per company website; independently unverifiable) | -Speed-first delivery culture may sacrifice architectural rigour for less-defined projects |
| +Mobile ML capability (TensorFlow Lite, Core ML) for on-device inference without cloud dependency | -Less depth in large-scale data engineering and MLOps infrastructure than data-first firms |
| +Top-ranked in multiple AI consulting company lists for 2026 | -EU delivery can create time-zone friction for US West Coast clients needing real-time collaboration |
| +Product engineering + ML under one roof eliminates integration handoff friction | |
| +Kraków location provides access to a deep Polish AI/ML talent pool |
Miquido vs alternatives
How Miquido compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Mid-market teams, specialist CV/time-series/LLM delivery. | Boutique ML depth, with access to the 25-year enterprise delivery experience of its parent company — a rare combination in the ML services market | 4.9 | Full comparison |
| LeewayHertz | Businesses, GenAI/LLM integration plus custom ML. | Among the earliest boutique firms to build a structured GenAI delivery framework — deep LLM orchestration and RAG pipeline experience | 4.1 | Full comparison |
| Scopic | Companies needing genuinely custom ML architectures. | Engineers custom ML architectures from the ground up — not fine-tuned wrappers — with 20 years of production delivery discipline | 4.6 | Full comparison |
| InData Labs | Complex ML problems, deep data-science expertise. | Boutique firm with a track record of solving atypical, high-complexity ML problems that generalist shops decline or under-deliver on | 4.6 | Full comparison |
| DATAFOREST | Mid-market companies, full ML pipeline ownership. | Structured MLaaS delivery model — one team owns data engineering, model development, and post-deployment monitoring end-to-end | 4.5 | Full comparison |
| Forte Group | Regulated finance/insurance firms, audit-ready ML governance. | ML delivery built for regulated environments — model risk governance, audit trails, and compliance-aligned architecture are built in, not bolted on | 4.5 | Full comparison |
| RTS Labs | High-growth US companies, production-accountable ML partner. | Small by choice, senior by design — every project is staffed with senior practitioners accountable for post-launch performance, not just the plan | 4.5 | Full comparison |
| Quantiphi | Enterprises, cloud-native ML, top-tier AWS/GCP credentials. | AWS Premier and four-time Google Cloud Partner of the Year — the highest independently verified cloud ML credentials in the market | 4.4 | Full comparison |
| N-iX | EU/US enterprises, large dedicated teams, competitive rates. | Scale and depth in one package — 2,000+ engineers with a mature ML practice and competitive EU delivery rates | 4.4 | Full comparison |
| Algoscale | Fortune 500 and growth-stage companies, cloud data lakehouse... | 100+ production ML deployments on AWS, Azure, and Snowflake — proven at enterprise scale with multiple cloud stacks | 4.3 | Full comparison |
| STX Next | Python-stack product companies, tightly integrated ML plus MLOps. | Europe's largest Python shop — ML is embedded in full-stack Python systems with MLOps, not delivered as an isolated model | 4.3 | Full comparison |
| Intellias | Enterprises, AWS-native ML, validated CV/NLP/RAG results. | AWS AI Services Competency with verified production benchmarks — 10x TCO reduction in aerial imagery and sub-8-second NLP query latency | 4.3 | Full comparison |
| ScienceSoft | Healthcare/finance orgs, HIPAA/PCI-DSS/SOC2-compliant ML. | Over 35 years of regulated IT delivery — compliance-aligned ML architecture is a core competency, not an add-on | 4.2 | Full comparison |
| Simform | Manufacturing/logistics enterprises, cloud-native ML plus IoT. | AWS Premier Partner specialising in connecting physical IoT sensor data to cloud-based ML models for predictive maintenance | 4.2 | Full comparison |
| Oxagile | Healthcare/media/retail enterprises, cost-effective Eastern European ML. | Strong connected-care and healthcare AI track record combined with 40–60% cost advantage versus US equivalents | 4.2 | Full comparison |
| Softeq | Companies building AI for edge and embedded hardware. | Hardware-to-cloud ML engineering — a rare full-stack capability covering embedded device AI through cloud model serving | 4.1 | Full comparison |
| Aimprosoft | SMBs, AI consulting and custom ML at accessible... | Full-cycle AI delivery from consulting through implementation, optimised for SMB budgets and timelines | 4.1 | Full comparison |
| Uvik Software | Teams with an existing ML codebase, embedded senior... | Senior-only ML engineer staffing — embedded in your stack, working in your tools, without agency overhead | 4.1 | Full comparison |
| Ciklum | FinTech, Retail, Healthcare enterprises — AI product engineering... | 25+ AI products in production combined with 3,000+ global engineers — enterprise AI scale without the big-four overhead | 4.1 | Full comparison |
| Iflexion | ML newcomers, AI strategy and scoping first. | Consulting-first model ensures the ML problem is correctly defined before engineering investment begins | 4.0 | Full comparison |
| Itransition | EU-operating enterprises, GDPR/EU AI Act-compliant ML. | EU regulatory compliance depth for ML — GDPR-aligned data architecture and EU AI Act readiness built into delivery | 4.0 | Full comparison |
| DataToBiz | Startups taking an ML idea to market-ready delivery. | Product-oriented ML delivery — combines AI strategy with full-cycle engineering to produce launchable products, not just models | 4.0 | Full comparison |
| BairesDev | Enterprises and scale-ups, fast teams, US time-zone aligned. | Latin American engineering delivery with US time-zone alignment — faster team ramp than Asian offshore with significant rate advantage versus US onshore | 4.0 | Full comparison |
| Andersen Lab | Enterprises, large-scale ML, Fortune-500 references, EU footprint. | Named client references including Siemens, S&P Global, and Ryanair — enterprise ML track record at the highest scale | 4.0 | Full comparison |
| Intuz | SMBs, US-headquartered AI/ML at accessible rates. | 1,700+ delivered projects for SMBs — the broadest SMB ML delivery track record in this list | 3.9 | Full comparison |
| Tredence | Fortune 500 enterprises, AI analytics and supply-chain ML. | Large specialised analytics and AI firm — enterprise supply chain ML and CX analytics depth with Fortune 500 client delivery track record | 3.9 | Full comparison |
| Codiant | Budget-conscious orgs, end-to-end ML delivery. | Cost-efficient end-to-end ML delivery covering all phases — discovery, build, integration, and optimisation — in a single engagement | 3.9 | Full comparison |
| GlobalLogic (Hitachi) | Global enterprises, massive-scale MLOps, Hitachi-backed. | Hitachi Group backing with 27,000 engineers — the scale and compliance posture of a major industrial conglomerate applied to enterprise ML | 3.9 | Full comparison |
| EPAM Systems | Global enterprises, complex AI products, governance at scale. | AI-native engineering practice at 50,000-person scale — the broadest talent pool and delivery capacity of any firm on this list | 3.8 | Full comparison |
| Cognizant | Fortune 500 enterprises, multi-year AI transformation programmes. | One of the world's largest AI & Analytics practices — Fortune 500 industry vertical depth and compliance credentials at 350,000-person delivery scale | 3.8 | Full comparison |
| Accenture | Global enterprises, governed GenAI and agentic AI at... | Accenture's global AI practice applies consulting strategy, industry domain expertise, and engineering delivery at 700,000-person scale — designed exclusively for enterprise | 3.8 | Full comparison |
| DataRobot | Enterprise data-science teams, governed AutoML platform. | Platform-driven ML — DataRobot's AutoML engine and MLOps governance layer enable internal data science teams to build and manage models at scale without per-project custom development | 3.8 | Full comparison |
Miquido FAQ
What is Miquido?
Miquido is a product and technology company founded in 2011 and headquartered in Kraków, Poland, with 200+ employees. The firm offers custom machine learning development alongside mobile and product engineering, making it a strong option when ML needs to be embedded within a mobile or SaaS product. Miquido is recognised for rapid generative AI delivery — offering GenAI app demos in two days and full products in four weeks — and has delivered for clients in finance, media, and healthcare.
How much does Miquido charge?
Miquido uses fixed project, t&m pricing. Minimum engagement starts at $30K. A discovery call is required to get project-specific quotes.
What tech stack does Miquido use?
Miquido works with TensorFlow, PyTorch, OpenAI, Hugging Face, AWS, GCP, TensorFlow Lite, Core ML. Primary industries served include Financial Services, Media & Entertainment, Healthcare & Life Sciences, Retail & E-commerce, SaaS & Technology.
Is Miquido right for enterprise?
Product companies, ML/GenAI embedded, fast time-to-demo. 200+ team size. Key consideration: Speed-first delivery culture may sacrifice architectural rigour for less-defined projects.
What are the best Miquido alternatives?
The best alternatives to Miquido depend on your use case. Top options are:
- Tensorway: boutique ml depth, with access to the 25-year enterprise delivery experience of its parent company — a rare combination in the ml services market
- LeewayHertz: among the earliest boutique firms to build a structured genai delivery framework — deep llm orchestration and rag pipeline experience
- Scopic: engineers custom ml architectures from the ground up — not fine-tuned wrappers — with 20 years of production delivery discipline
Compare Miquido with other Machine Learning Development companies
Miquido vs Tensorway Miquido vs LeewayHertz Miquido vs Scopic Miquido vs InData Labs Miquido vs DATAFOREST Miquido vs Forte Group Miquido vs RTS Labs Miquido vs Quantiphi Miquido vs N-iX Miquido vs Algoscale Miquido vs STX Next Miquido vs Intellias Miquido vs ScienceSoft Miquido vs Simform Miquido vs Oxagile Miquido vs Softeq Miquido vs Aimprosoft Miquido vs Uvik Software Miquido vs Ciklum Miquido vs Iflexion Miquido vs Itransition Miquido vs DataToBiz Miquido vs BairesDev Miquido vs Andersen Lab Miquido vs Intuz Miquido vs Tredence Miquido vs Codiant Miquido vs GlobalLogic (Hitachi) Miquido vs EPAM Systems Miquido vs Cognizant Miquido vs Accenture Miquido vs DataRobot