Best ML Development Services

Space-O Technologies vs Intellias: full comparison for 2026

Last updated: July 2026

Quick verdict

Space-O Technologies (4.0/5) edges ahead of Intellias (3.7/5) overall. Space-O Technologies is the better choice for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement.. Intellias is the stronger option for automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage.. The right choice depends on your project size, budget, and required tech stack.

Space-O Technologies vs Intellias: head-to-head summary

Criterion Space-O Technologies Intellias
Founded 2010 2002
HQ Ahmedabad, India Sliema, Malta
Team size 140+ 2,961
Rating 4.0 / 5 3.7 / 5
Best for Companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement. Automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage.
Pricing model Project-based, dedicated team Time & materials, dedicated team
Min. engagement Not published Not published
Primary tech stack TensorFlow, Keras, OpenAI API Python, AWS, Azure
Industries served Healthcare, EdTech, Retail & E-commerce, Travel & Hospitality Automotive, Manufacturing, FinTech, Retail & E-commerce

Space-O Technologies vs Intellias: overview

Space-O Technologies

Space-O Technologies was founded in 2010 by Rakeshkumar Patel and Atit Tusharbhai Purani, growing to roughly 140 full-stack engineers and AI specialists with offices in the US, Canada, and India. The company built its reputation on mobile app development (including early on-demand apps and EdTech products) before extending into machine learning on both neural and non-neural networks, working with frameworks including Keras, Caffe, and TensorFlow, plus more recent integration of OpenAI's GPT, Whisper, and LangChain. Its origin as a mobile-app shop means ML is a newer, added capability rather than the company's founding focus.

Intellias

Intellias was founded in 2002 in Lviv, Ukraine by Michael Puzrakov and Vitaly Sedler and now lists its headquarters in Sliema, Malta, with a workforce exceeding 2,961 employees (some sources cite 3,000+). The company specializes in IoT, artificial intelligence, machine learning, big data, cloud computing, data science, and DevOps, and has been listed among top service providers by Clutch, IAOP, and the GSA UK Awards. Its automotive and mobility-sector heritage gives it particular depth in embedded/IoT-adjacent ML applications relative to more general-purpose AI consultancies.

Services and capabilities: Space-O Technologies vs Intellias

Capability Space-O Technologies Intellias
Custom ML Models
Computer Vision
NLP
MLOps
Generative AI
AI Consulting

Tech stack comparison: Space-O Technologies vs Intellias

Framework / platform Space-O Technologies Intellias
TensorFlow
PyTorch N/A N/A
AWS N/A
Azure N/A
Google Cloud N/A N/A
LangChain N/A
Hugging Face N/A N/A
Kubernetes N/A N/A

Pricing comparison: Space-O Technologies vs Intellias

Criterion Space-O Technologies Intellias
Minimum engagement Not published Not published
Engagement models Project-based, Dedicated team, Fixed project Dedicated team, Time & materials, Staff augmentation
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Space-O Technologies vs Intellias

Dimension Space-O Technologies Intellias
Best company size Startup to mid-market Startup to mid-market
Best industries Healthcare, EdTech, Retail & E-commerce Automotive, Manufacturing, FinTech
Best use cases Company needs an ML feature (recommendation, prediction, chatbot) built directly into a new or existing mobile app., EdTech or travel company wants a single vendor for both application development and embedded AI features. Automotive or mobility company needs ML development from a firm with genuine embedded-systems and IoT heritage., Enterprise wants a vendor recognized by three independent bodies (Clutch, IAOP, GSA UK) rather than one.
Typical project type Project-based Dedicated team

Space-O Technologies vs Intellias: pros and cons

Space-O Technologies
+ 15 years of product-delivery history (since 2010), with a track record that includes early on-demand and EdTech app development.
+ 300+ delivered software solutions and 1,200+ clients gives it a broad delivery pattern library.
+ Integrates modern generative AI tooling (GPT, Whisper, LangChain) alongside classical ML frameworks (Keras, Caffe, TensorFlow).
+ Offices across US, Canada, and India provide time-zone coverage for North American clients.
- Company's core identity and longest track record is in mobile app development, not ML — AI/ML is a newer, extended service line.
- 140-person team spread across app development, AI development, and other services means ML-specific bench depth is smaller than the total headcount suggests.
Intellias
+ 22+ years of operating history (since 2002) with founders still traceable to the company's Lviv origins.
+ 2,961-person workforce provides strong delivery capacity for large, multi-workstream enterprise programs.
+ Recognized among top service providers by Clutch, IAOP, and the GSA UK Awards — three independent bodies rather than one.
+ Automotive and IoT sector depth differentiates it from generalist ML consultancies for embedded/connected-device use cases.
- Legal headquarters in Sliema, Malta while founding and significant delivery capacity remains tied to Lviv, Ukraine — confirm contracting jurisdiction.
- At nearly 3,000 employees, AI/ML is one of several core specializations (IoT, big data, cloud, DevOps) rather than a standalone focus.

Who should choose Space-O Technologies?

Space-O Technologies is the right choice for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement..

15 years of mobile/software product delivery experience (since 2010) with ML added as a production-application capability.. Minimum engagement starts at Not published. Works best with clients in Healthcare, EdTech, Retail & E-commerce, Travel & Hospitality.

Who should choose Intellias?

Intellias is the right choice for automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage..

Strong automotive/mobility and IoT sector heritage, giving it differentiated depth in embedded and connected-device ML use cases.. Minimum engagement starts at Not published. Works best with clients in Automotive, Manufacturing, FinTech, Retail & E-commerce.

Decision matrix: Space-O Technologies vs Intellias

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Space-O Technologies
You need a large dedicated team for an ongoing programme Space-O Technologies
Your budget is at the lower end Compare: Space-O Technologies (Not published) vs Intellias (Not published)
You need specialist depth in a specific vertical Space-O Technologies
You need production MLOps support after model launch Both offer MLOps support
You need consulting before committing to a build Both may offer discovery engagements

Use case fit: Space-O Technologies vs Intellias

Use case Space-O Technologies fit Intellias fit Winner
Company needs an ML feature (recommendation, prediction, chatbot) built directly into a new or existing mobile app. Strong Strong Both equally
EdTech or travel company wants a single vendor for both application development and embedded AI features. Strong Limited Space-O Technologies
Automotive or mobility company needs ML development from a firm with genuine embedded-systems and IoT heritage. Limited Strong Intellias
Enterprise wants a vendor recognized by three independent bodies (Clutch, IAOP, GSA UK) rather than one. Limited Strong Intellias
Fixed-scope ML build Limited Limited Both equally
Ongoing model retraining Limited Limited Both equally

Verdict: Space-O Technologies vs Intellias

Space-O Technologies (4.0/5) is the stronger overall choice for most Machine Learning Development projects. 15 years of mobile/software product delivery experience (since 2010) with ML added as a production-application capability.. It is best for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement..

Intellias (3.7/5) is the better choice when automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage.. If your situation matches those criteria, Intellias is a competitive option.

Related comparisons

Space-O Technologies vs Intellias FAQ

Is Space-O Technologies better than Intellias?

Space-O Technologies (4.0/5) scores higher overall, but "better" depends on your use case. Space-O Technologies is better for companies that need machine learning embedded into a mobile or web application, not a standalone ML research engagement.. Intellias is better for automotive, mobility, and IoT companies wanting ML development from a firm with deep embedded-systems heritage..

How do Space-O Technologies and Intellias differ in pricing?

Space-O Technologies uses project-based, dedicated team pricing with a minimum engagement of Not published. Intellias uses time & materials, dedicated team pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Space-O Technologies or Intellias?

Intellias is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.

What are the main differences between Space-O Technologies and Intellias?

Space-O Technologies's primary differentiator is: 15 years of mobile/software product delivery experience (since 2010) with ml added as a production-application capability.. Intellias's primary differentiator is: strong automotive/mobility and iot sector heritage, giving it differentiated depth in embedded and connected-device ml use cases.. They also differ in team size (140+ vs 2,961), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, EdTech vs Automotive, Manufacturing).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.