Addepto
Warsaw AI consultancy specializing in taking machine learning from proof-of-concept into enterprise production.
Founded 2017 | Warsaw, Poland | 50–249 employees | Last updated: July 2026
ai-consultingml-developmentmlopsdata-engineering
What is Addepto?
Addepto is a Warsaw, Poland AI consultancy founded in 2017 that explicitly positions its value around production-grade delivery — moving clients from proof-of-concept to production — rather than research exploration. It covers AI consulting, generative AI development, data engineering, MLOps, document processing, and computer vision, serving aviation, manufacturing, automotive, finance, retail, healthcare, and logistics clients. Addepto is a GoodFirms top-rated firm for Big Data and Business Intelligence services, with a 50–249 employee band per Clutch.
Addepto was founded in 2017 and is headquartered in Warsaw, Poland. The firm employs 50–249 people and works primarily with clients in Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics sectors. Its primary differentiator is: Explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ML pilots never reach deployment..
Addepto tech stack and services
PythonMLOps pipelinesAWSAzureGoogle CloudComputer vision frameworks
| Service area | Details |
|---|---|
| Computer vision for document processing | Available for Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics clients |
| MLOps pipeline hardening for existing proof-of-concepts | Available for Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics clients |
| Business intelligence and data governance builds | Available for Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics clients |
| Enterprise AI transformation programs | Available for Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics clients |
Addepto use cases
Short answer: Addepto is best suited for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline..
| Use case | Industries | Approach |
|---|---|---|
| Computer vision for document processing | Aviation, Manufacturing | Python, MLOps pipelines |
| MLOps pipeline hardening for existing proof-of-concepts | Aviation, Manufacturing | Python, MLOps pipelines |
| Business intelligence and data governance builds | Aviation, Manufacturing | Python, MLOps pipelines |
| Enterprise AI transformation programs | Aviation, Manufacturing | Python, MLOps pipelines |
Addepto pricing
Short answer: Addepto uses a fixed project, time & materials pricing approach. Minimum engagement starts at $10,000+.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $10,000+ | Well-defined scope |
| Time & Materials | 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 |
|---|---|
| +Broad industry coverage from aviation to legal shows delivery flexibility beyond a single vertical | -Broad industry spread can mean less depth in any single regulated vertical than a specialist boutique |
| +Explicit MLOps and production focus addresses the common 'stuck in proof-of-concept' failure mode | -Exact team size within the 50–249 Clutch band is not broken out by function |
| +$10K entry point is accessible for a mid-market pilot engagement | -Public case studies are largely testimonial-based rather than published with hard metrics |
| +GoodFirms top-rated recognition for Big Data and Business Intelligence services |
Addepto vs alternatives
How Addepto compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| dida Datenschmiede | Organizations that need a tightly-scoped, research-grade ML solution... | Team composed primarily of mathematicians and physicists, explicitly rejecting black-box tooling in favor of custom-built models as its sole service line. | 4.8 | Full comparison |
| Tensorway | Mid-market fintech, energy, and supply-chain companies that want... | Spun out of Anadea's applied R&D unit in 2019, giving it a mature delivery bench uncommon for a five-year-old AI boutique. | 4.6 | Full comparison |
| NILG.AI | Companies earlier in their AI adoption curve that... | Founder-led by a University of Porto PhD with a public AI-education arm (100K+ YouTube subscribers, Microsoft education partner) that doubles as a technical credibility signal. | 4.5 | Full comparison |
| Neurons Lab | Financial-services firms that need agentic AI systems with... | Positions itself as an end-to-end AI enablement partner specifically for financial services, with governance and compliance tooling built into the core offer rather than added on. | 4.5 | Full comparison |
| InData Labs | Companies wanting a decade-plus data science track record... | Runs its own R&D center rather than purely project-based delivery, spanning generative AI/GPT integration through classic predictive analytics and computer vision. | 4.4 | Full comparison |
| Xomnia | Dutch and Northwest European enterprises wanting a single... | Acquired Aurai in 2025 specifically to consolidate strategy, platform, and applied-AI capability under one roof as it scales toward regional market leadership. | 4.3 | Full comparison |
| WeAreBrain | Startups and scale-ups wanting AI-native product development combined... | Frames itself around culture and retention — 'a winning team, not an agency' — with a long average client tenure as central to its pitch alongside technical delivery. | 4.3 | Full comparison |
| Deeper Insights | Enterprises across healthcare, real estate, and financial services... | Team holds 500+ citations and patents globally (per company website), signaling research depth rather than a purely delivery-focused staffing model. | 4.3 | Full comparison |
| Alexander Thamm | Large German and DACH-region enterprises — especially automotive... | 'Whitebox solutions' positioning emphasizes transparency and manufacturer independence, backed by 3,500+ completed projects and blue-chip automotive clients. | 4.2 | Full comparison |
| Nexocode | Startups and scale-ups wanting a small, senior AI... | Explicitly flat organizational structure with no traditional management hierarchy — every team member is described as equally involved in growth and delivery decisions. | 4.2 | Full comparison |
| Predli | Organizations wanting a structured path from first AI... | 'Predli Studio' is a dedicated build function that turns AI strategy directly into production-grade custom solutions, rather than handing delivery to a separate vendor. | 4.2 | Full comparison |
| Synergy Labs | French and EU businesses wanting practical, dashboard- and... | Focuses specifically on business-facing applied ML — smart dashboards, customer segmentation, recommendation engines — built to EU compliance rules, rather than broad AI R&D. | 4.1 | Full comparison |
| xtream | Italian and pan-European scale-ups wanting AI features embedded... | Combines UX design, product management, and software engineering with applied ML and BI — AI is delivered as part of a full digital-product build, not a bolt-on service. | 4.1 | Full comparison |
| element61 | Belgian and Benelux enterprises wanting a long-established analytics... | Started as an analytics and performance-management consultancy in 2007 and layered data science and AI on top of an already-mature BI practice, combining both under one roof. | 4.1 | Full comparison |
| Miquido | Companies wanting AI and ML features — RAG,... | Offers on-device AI development and AI guardrails alongside core ML, computer vision, and NLP work — a more product-engineering-centric AI offering than pure consulting-first competitors. | 4.1 | Full comparison |
| Neoteric | Companies wanting a well-reviewed, mid-size Polish AI and... | 4.9/5 rating across 70 verified Clutch reviews and 300+ completed projects across five continents gives an unusually large, independently verifiable review base for a company of this size. | 4.0 | Full comparison |
| Grape Up | Automotive and finance enterprises wanting agentic AI and... | Built its own productized platforms (Databoostr, Cloudboostr) alongside custom delivery — a hybrid product-plus-services model less common among pure consultancies on this list. | 4.0 | Full comparison |
| Deviniti | Enterprises in regulated or complex sectors wanting generative... | 50+ Atlassian-certified professionals and Atlassian Partner of the Year finalist status give it unusually strong enterprise-IT integration credibility alongside its generative AI practice and Bielik.AI open-source contributions. | 4.0 | Full comparison |
| STX Next | Enterprises wanting Python-native ML and AI engineering from... | Built and open-sourced DeepNext, an autonomous AI developer agent, and holds AWS Advanced Tier, Snowflake, Databricks, Azure, and Amazon Bedrock partnerships simultaneously. | 4.0 | Full comparison |
| CN Group CZ | Nordic, German, and Austrian enterprises wanting an established,... | Combines Scandinavian management style with Czech, Slovak, and Romanian engineering talent, and layers AI/ML onto a much older core business in embedded systems and industrial automation. | 3.9 | Full comparison |
| ASSIST Software | Manufacturing and agriculture clients in the DACH region... | Runs 25+ active R&D projects and participates in 25+ EU-funded research programs alongside 160+ research-institution partnerships — an unusually research-heavy profile for a 30+ year old nearshore vendor. | 3.9 | Full comparison |
| Software Mind | Large enterprises wanting AI/ML delivered alongside broader custom... | 48-month average client relationship length and ISO 9001/14001/27001 certification stack signal an enterprise-process-mature vendor built for long-term programs rather than short AI pilots. | 3.9 | Full comparison |
| Future Processing | Insurance, finance, and energy enterprises wanting an outcome-based... | Publicly states that 95% of generative AI pilots deliver no measurable return and positions its own outcome-based delivery approach against that failure pattern, backed by named case studies with hard percentage metrics. | 3.9 | Full comparison |
| SPD Technology | Fintech and payments companies wanting AI/ML delivered by... | Secured direct partnerships with OpenAI, Anthropic, and AWS specifically to reinforce its cloud and AI/ML capabilities — a more direct foundation-model-vendor relationship than most peers on this list disclose. | 3.9 | Full comparison |
| Zühlke | Large regulated enterprises — medtech, finance, industrial —... | Founded in 1968 as a product-innovation engineering firm, giving it a far longer institutional track record than any other company on this list — AI/ML is one current-generation capability within a much broader innovation-consulting practice. | 3.9 | Full comparison |
| Arnia Software | Companies needing deep R&D-level engineering — database engines,... | Machine learning expertise grew out of Arnia's original R&D work in database engines and operating systems, giving it lower-level systems engineering depth uncommon among application-focused AI vendors on this list. | 3.8 | Full comparison |
| Reaktor | Enterprises wanting AI capability embedded within a broader... | Co-created 'Elements of AI,' a free AI literacy MOOC with the University of Helsinki taken by over half a million people worldwide — a public-education contribution unmatched by any other company on this list. | 3.8 | Full comparison |
| Framna | Nordic and Benelux enterprises wanting mobile-first digital product... | Formed in 2023 through the merger of three established agencies backed by Waterland Private Equity, giving it unusually broad simultaneous coverage of Sweden, Denmark, the Netherlands, and Poland under one group. | 3.8 | Full comparison |
| N-iX | Large enterprises wanting AI-augmented software engineering at significant... | Legally headquartered in Valletta, Malta, with its primary engineering hub historically in Lviv, Ukraine; relocated 600+ Ukrainian engineers to safety in 2022 without dropping a single client project, and reports zero delivery disruptions since founding in 2002. | 3.8 | Full comparison |
| Sigma Software | Large enterprises wanting a Swedish-incorporated, EU-contractable IT consultancy... | 60% owned by the Swedish Sigma Group since 2006, giving Sigma Software a Swedish corporate parent and legal entity while its founding engineering culture and historical delivery base trace to Kharkiv, Ukraine. | 3.7 | Full comparison |
| Nordcloud (an IBM Company) | Large enterprises already committed to a major public... | Acquired by IBM in 2020 and now operates as an IBM subsidiary, giving it direct backing from one of the largest enterprise technology vendors globally, while holding all three major cloud certifications simultaneously. | 3.7 | Full comparison |
Addepto FAQ
What is Addepto?
Addepto is a Warsaw, Poland AI consultancy founded in 2017 that explicitly positions its value around production-grade delivery — moving clients from proof-of-concept to production — rather than research exploration. It covers AI consulting, generative AI development, data engineering, MLOps, document processing, and computer vision, serving aviation, manufacturing, automotive, finance, retail, healthcare, and logistics clients. Addepto is a GoodFirms top-rated firm for Big Data and Business Intelligence services, with a 50–249 employee band per Clutch.
How much does Addepto charge?
Addepto uses fixed project, time & materials pricing. Minimum engagement starts at $10,000+. A discovery call is required to get project-specific quotes.
What tech stack does Addepto use?
Addepto works with Python, MLOps pipelines, AWS, Azure, Google Cloud, Computer vision frameworks. Primary industries served include Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics.
Is Addepto right for enterprise?
Mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline.. 50–249 team size. Key consideration: Broad industry spread can mean less depth in any single regulated vertical than a specialist boutique.
What are the best Addepto alternatives?
The best alternatives to Addepto depend on your use case. Top options are:
- dida Datenschmiede: team composed primarily of mathematicians and physicists, explicitly rejecting black-box tooling in favor of custom-built models as its sole service line.
- Tensorway: spun out of anadea's applied r&d unit in 2019, giving it a mature delivery bench uncommon for a five-year-old ai boutique.
- NILG.AI: founder-led by a university of porto phd with a public ai-education arm (100k+ youtube subscribers, microsoft education partner) that doubles as a technical credibility signal.
Compare Addepto with other Machine Learning Development companies
Addepto vs dida Datenschmiede Addepto vs Tensorway Addepto vs NILG.AI Addepto vs Neurons Lab Addepto vs InData Labs Addepto vs Xomnia Addepto vs WeAreBrain Addepto vs Deeper Insights Addepto vs Alexander Thamm Addepto vs Nexocode Addepto vs Predli Addepto vs Synergy Labs Addepto vs xtream Addepto vs element61 Addepto vs Miquido Addepto vs Neoteric Addepto vs Grape Up Addepto vs Deviniti Addepto vs STX Next Addepto vs CN Group CZ Addepto vs ASSIST Software Addepto vs Software Mind Addepto vs Future Processing Addepto vs SPD Technology Addepto vs Zühlke Addepto vs Arnia Software Addepto vs Reaktor Addepto vs Framna Addepto vs N-iX Addepto vs Sigma Software Addepto vs Nordcloud (an IBM Company)
Last reviewed: July 2026. Verify all details directly with Addepto before making a decision.