Addepto
Warsaw-based AI boutique with deep expertise in ML for finance, energy, and retail.
Founded 2016 | Warsaw, Poland | 50–200 employees
custom-mlml-consultingdeep-learninggenerative-aipredictive-analyticsdata-engineering
What is Addepto?
Addepto is a Poland-based AI consulting and development firm focused on end-to-end machine learning solutions for mid-market and enterprise clients. The company specializes in building data pipelines, custom ML models, and decision-support tools with particular depth in financial services, energy, and retail — industries where regulatory awareness and data governance are non-negotiable. Addepto covers the full stack from data engineering through model development, deployment, and integration.
Addepto was founded in 2016 and is headquartered in Warsaw, Poland. The firm employs 50–200 people and works primarily with clients in fintech, energy, retail, manufacturing, logistics sectors. Its primary differentiator is: End-to-end AI/ML delivery with particular sector depth in financial services and energy — industries that require compliance sophistication alongside technical capability.
Addepto tech stack and services
PythonTensorFlowPyTorchScikit-LearnOpenAIHugging FaceAWSAzureGCPApache SparkAirflow
| Service area |
|---|
| Custom ML Development |
| ML Consulting |
| Deep Learning |
| Generative AI |
| Predictive Analytics |
| Data Engineering |
Addepto use cases
Short answer: Addepto is best suited for Finance, energy, retail — bespoke ML with pipeline support.
| Use case |
|---|
| Credit risk scoring and fraud detection model development for fintech platforms |
| Energy demand forecasting and grid optimization using time-series ML models |
| Retail recommendation engine and dynamic pricing model development |
| Custom LLM integration for regulated-industry document processing |
| Decision-support ML tools for operations teams in manufacturing or logistics |
Addepto pricing
Short answer: Addepto uses a fixed project, t&m, dedicated team pricing approach. Minimum engagement starts at $20K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $20K | Well-defined scope |
| T&M | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
Addepto does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Addepto pros and cons
| Advantages | Things to consider |
|---|---|
| +Genuine depth in finance and energy ML — not a generalist firm claiming vertical expertise | -Smaller team than enterprise-tier firms; large-scale concurrent programmes may strain capacity |
| +Covers the full stack from data pipeline architecture through model deployment | -Less US-based client management than North American competitors |
| +Generative AI capability alongside classical ML for hybrid solution architectures | -Limited public case studies compared to larger firms with dedicated marketing teams |
| +Warsaw delivery hub provides competitive rates with EU-based data handling | |
| +Accessible minimum engagement for early-stage ML projects or POCs |
Addepto vs alternatives
How Addepto compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Dedicated ML boutique, strategy through production MLOps. | ML-only focus with a dedicated specialist team backed by 25 years of the parent company software delivery infrastructure — unusually deep for a firm of this size | 4.8 | Full comparison |
| LeewayHertz | Enterprises, end-to-end AI delivery, Fortune 500 clients. | Product-centric AI delivery culture with verified Fortune 500 client references including ESPN, Siemens, and 3M — now operating within The Hackett Group | 4.0 | Full comparison |
| InData Labs | Mid-market orgs, complex ML, deep data-science expertise. | Pure-play ML boutique with a measurably higher specialist-to-generalist ratio than typical service firms, confirmed by Clutch as a top AI service provider | 4.5 | Full comparison |
| HatchWorks AI | Companies wanting AI-native, generative-AI-embedded delivery. | Clutch #1 AI Services Company with a proprietary Generative Driven Development methodology claimed to reduce delivery time by 30–50% (per company website; independently unverifiable) | 4.4 | Full comparison |
| STX Next | Orgs needing ML operationalized in Python-native systems. | Europe's largest Python-specialist firm uniquely positioned to embed ML into production software without the integration friction that plagues pure-play ML boutiques | 4.3 | Full comparison |
| Tredence | Enterprises, last-mile ML adoption, supply chain and retail. | Industry-specific AI accelerators and a proven focus on last-mile ML adoption, closing the execution gap between data science output and real business value | 4.3 | Full comparison |
| DataForest | Data-first companies, robust engineering foundation for ML. | Data engineering-first approach builds pipeline and data quality foundations before model development, addressing the root cause of most ML project failures | 4.2 | Full comparison |
| Forte Group | Orgs wanting Tier-1 rigor, specialist agility, roadmap to... | Structured AI service lines with Tier 1 delivery rigor and specialist consultancy agility — serving organizations that need both without enterprise-tier pricing | 4.1 | Full comparison |
| Binariks | Healthcare, fintech, insurance — compliance-first ML engineering. | Compliance-first ML engineering for regulated industries — governance and audit trails are built in from the architecture stage, not retrofitted after launch | 4.1 | Full comparison |
| Softeq | Hardware and industrial companies, edge ML on embedded... | Unique capability to combine hardware design expertise with ML engineering, deploying models at the edge where cloud-only ML firms cannot operate | 4.1 | Full comparison |
| Markovate | Retail, travel, fitness — recommendation engines, 300+ projects. | 300+ delivered projects spanning recommendation systems, computer vision, and dynamic pricing, with deeper consumer-facing ML specialization than most comparably sized firms | 4.0 | Full comparison |
| ScienceSoft | Established enterprises, 35+ years, stable US vendor. | 35+ years of enterprise delivery experience with a mature ML practice — providing compliance readiness, institutional knowledge, and process maturity rare in younger ML-focused competitors | 4.0 | Full comparison |
| Miquido | Product teams, ML in polished products, Google-certified. | Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms | 4.0 | Full comparison |
| Simform | Industrial and enterprise, cloud-native AWS ML at scale. | AWS Premier Partner with 1,000+ engineers and documented depth in industrial IoT ML — connecting physical sensor streams to cloud ML inference at production scale | 3.9 | Full comparison |
| Intuz | SMBs, fixed-price discovery, 1,700+ projects. | 1,700+ project track record with a discovery-first engagement model making enterprise-grade ML accessible to SMBs through risk-reduced fixed-price POC phases | 3.9 | Full comparison |
| Scopic | Orgs wanting custom ML, 20+ years, strong computer... | 20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare | 3.9 | Full comparison |
| N-iX | Enterprises, large-scale Eastern-Europe ML engineering capacity. | 2,400+ engineers with deep specialization in scalable AI architectures, able to field large dedicated teams for complex multi-year ML programmes at competitive Eastern European rates | 3.9 | Full comparison |
| Oxagile | Media, AdTech, sports — video ML, 20+ years... | 20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics | 3.8 | Full comparison |
| Innowise | Banking, agriculture, healthcare — compliance-aware ML. | Cross-vertical ML delivery with documented case studies in banking automation, agricultural forecasting, and healthcare diagnostics — unusual breadth across regulated industries | 3.9 | Full comparison |
| Intellectsoft | Fintech, healthcare, construction — ML in enterprise ecosystems. | Palo Alto HQ with 10 global delivery offices combining US-based account management with competitive Eastern European delivery rates for enterprise ML programmes | 3.8 | Full comparison |
| DataRoot Labs | Startups and scale-ups, AI strategy plus execution, accessible. | One of Ukraine's most recognized ML consultancies — combining strategy-level AI advisory with hands-on engineering, a combination rare at this team size and price point | 3.8 | Full comparison |
| Itransition | Enterprises, ML in legacy systems, 25+ years delivery. | 25+ years of enterprise software delivery with five dedicated R&D labs, giving clients a mature delivery operation with advanced ML research support at competitive rates | 3.9 | Full comparison |
| 10Pearls | US enterprises and government contractors, AI-native, LATAM delivery. | AI-native engineering culture with four CRN Solution Provider 500 recognitions and 1,400+ experts spanning North America and LATAM for enterprise AI programmes | 3.8 | Full comparison |
| Coherent Solutions | Microsoft-stack enterprises, #1 Twin Cities IT firm. | Ranked #1 IT consulting firm in the Twin Cities five times in six years with 2,000+ engineers across 10 development centers, offering enterprise ML at competitive rates | 3.8 | Full comparison |
| Iflexion | US orgs, ML within custom enterprise software systems. | 25 years of enterprise software delivery with 850+ professionals embedding ML into complete systems rather than delivering standalone models that require separate integration work | 3.7 | Full comparison |
| Appinventiv | Global businesses, mobile-first ML, five-continent delivery. | 1,600+ specialists with a mobile-first AI approach and global footprint delivering 1,000+ digital assets with embedded ML — strong for consumer-facing AI product work | 3.8 | Full comparison |
| Avenga | Telco, banking, automotive enterprises — 6,000+ engineer scale. | 6,000+ specialists across 44 delivery centers formed through PE-backed acquisitions, providing enterprise-scale AI delivery capacity — though cultural integration across legacy entities is ongoing | 3.7 | Full comparison |
| BairesDev | Companies wanting rapid ML scale-up, LATAM nearshore, US... | 4,000+ ML-capable LATAM engineers in US time zones with 1,200+ completed projects, enabling rapid scale-up for organizations that need to grow their ML capacity fast | 3.7 | Full comparison |
| Turing | Teams needing pre-vetted senior ML developers, staff augmentation. | AI-powered vetting platform screening 3M+ global ML developers to place the top 1% directly in client engineering teams at rates competitive with US in-house hiring | 3.7 | Full comparison |
| EPAM Systems | Large enterprises, Fortune 500 scale, global compliance. | 62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes | 3.9 | Full comparison |
Addepto FAQ
What is Addepto?
Addepto is a Poland-based AI consulting and development firm focused on end-to-end machine learning solutions for mid-market and enterprise clients. The company specializes in building data pipelines, custom ML models, and decision-support tools with particular depth in financial services, energy, and retail — industries where regulatory awareness and data governance are non-negotiable. Addepto covers the full stack from data engineering through model development, deployment, and integration.
How much does Addepto charge?
Addepto uses fixed project, t&m, dedicated team pricing. Minimum engagement starts at $20K. A discovery call is required to get project-specific quotes.
What tech stack does Addepto use?
Addepto works with Python, TensorFlow, PyTorch, Scikit-Learn, OpenAI, Hugging Face, AWS, Azure, GCP, Apache Spark, Airflow. Primary industries served include fintech, energy, retail, manufacturing, logistics.
Is Addepto right for enterprise?
Finance, energy, retail — bespoke ML with pipeline support. 50–200 team size. Key consideration: Smaller team than enterprise-tier firms; large-scale concurrent programmes may strain capacity.
What are the best Addepto alternatives?
The best alternatives to Addepto depend on your use case. Top options are:
- Tensorway: ml-only focus with a dedicated specialist team backed by 25 years of the parent company software delivery infrastructure — unusually deep for a firm of this size
- LeewayHertz: product-centric ai delivery culture with verified fortune 500 client references including espn, siemens, and 3m — now operating within the hackett group
- InData Labs: pure-play ml boutique with a measurably higher specialist-to-generalist ratio than typical service firms, confirmed by clutch as a top ai service provider
Compare Addepto with other Machine Learning Development companies
Addepto vs Tensorway Addepto vs LeewayHertz Addepto vs InData Labs Addepto vs HatchWorks AI Addepto vs STX Next Addepto vs Tredence Addepto vs DataForest Addepto vs Forte Group Addepto vs Binariks Addepto vs Softeq Addepto vs Markovate Addepto vs ScienceSoft Addepto vs Miquido Addepto vs Simform Addepto vs Intuz Addepto vs Scopic Addepto vs N-iX Addepto vs Oxagile Addepto vs Innowise Addepto vs Intellectsoft Addepto vs DataRoot Labs Addepto vs Itransition Addepto vs 10Pearls Addepto vs Coherent Solutions Addepto vs Iflexion Addepto vs Appinventiv Addepto vs Avenga Addepto vs BairesDev Addepto vs Turing Addepto vs EPAM Systems