Best ML Model Development Companies

ELEKS vs HCLTech: full comparison for 2026

Last updated: July 2026

Quick verdict

ELEKS (4.1/5) edges ahead of HCLTech (3.9/5) overall. ELEKS is the better choice for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. HCLTech is the stronger option for very large enterprises wanting a full-stack AI vendor spanning hardware/chip-level work through to business process optimization.. The right choice depends on your project size, budget, and required tech stack.

ELEKS vs HCLTech: head-to-head summary

Criterion ELEKS HCLTech
Founded 1991 1976
HQ Tallinn, Estonia (engineering hub: Lviv, Ukraine) Noida, India
Team size 1,001–5,000 10,000+
Rating 4.1 / 5 3.9 / 5
Best for Enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor. Very large enterprises wanting a full-stack AI vendor spanning hardware/chip-level work through to business process optimization.
Pricing model Time & Material, Fixed project Not published; enterprise project engagements
Min. engagement Not published Not published
Primary tech stack Python, Cloud ML platforms (AWS/Azure/GCP), Data engineering tooling Amazon Bedrock, Amazon SageMaker, Amazon Q
Industries served Financial services, Healthcare, Manufacturing, Insurance Manufacturing, Financial services, Telecommunications, Automotive

ELEKS vs HCLTech: overview

ELEKS

ELEKS is a long-running European software engineering company founded in 1991, with corporate presence in Tallinn, Estonia and its largest engineering hub in Lviv, Ukraine, alongside additional offices across Europe and North America. The company reports more than 2,000 employees and operates a dedicated data science and AI practice layered onto its broader enterprise software engineering services. Its history predates the modern AI/ML consulting wave by roughly three decades, giving it an unusually long operating track record compared to most peers in this list.

HCLTech

HCLTech traces its origins to 1976 and formally entered the software services business in 1991, headquartered in Noida, India, with more than 224,000 employees globally. The company offers what it describes as an end-to-end AI capability stack spanning chip development through business process optimization, anchored by two proprietary platforms: Graviton, aimed at streamlining AI and machine learning development, and AION, an AI lifecycle management platform. HCLTech holds multiple AWS competencies and has built generative AI solutions using Amazon CodeWhisperer, Amazon Bedrock, Amazon SageMaker, and Amazon Q.

Services and capabilities: ELEKS vs HCLTech

Capability ELEKS HCLTech
Custom model training
Fine-tuning & adaptation
MLOps pipeline
Model deployment & serving
Data engineering for ML
ML infrastructure management
Computer vision
NLP & LLM development
Forecasting & time-series modeling
ML strategy consulting

Tech stack comparison: ELEKS vs HCLTech

Framework / platform ELEKS HCLTech
PyTorch N/A N/A
TensorFlow N/A N/A
MLflow N/A N/A
AWS SageMaker N/A N/A
Amazon Bedrock N/A
Google Cloud N/A N/A
Microsoft Azure N/A N/A
Kubernetes N/A
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: ELEKS vs HCLTech

Criterion ELEKS HCLTech
Minimum engagement Not published Not published
Engagement models Time & Material, Fixed project, Dedicated team Enterprise project engagement, Managed AI services
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: ELEKS vs HCLTech

Dimension ELEKS HCLTech
Best company size Startup to mid-market Enterprise
Best industries Financial services, Healthcare, Manufacturing Manufacturing, Financial services, Telecommunications
Best use cases Running an enterprise-scale data science initiative alongside a broader software modernization program, Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components Very large manufacturing or automotive enterprises needing a chip-to-cloud AI vendor, Deploying generative AI solutions using Amazon Bedrock, SageMaker, and Q at enterprise scale
Typical project type Time & Material Enterprise project engagement

ELEKS vs HCLTech: pros and cons

ELEKS
+ Over three decades of continuous operation, unusually long for this category.
+ Large engineering bench (2,000+ employees) supports substantial delivery capacity.
+ Data science practice is embedded within a mature enterprise software engineering organization.
+ Multi-region European and North American office footprint.
- AI/ML is one practice area within a much broader enterprise software portfolio, not the company's primary specialization.
- Specific, named ML case studies with quantified outcomes are limited in available public sources.
- Pricing minimums are not published.
- Long operating history does not necessarily translate into deep modern ML/LLM specialization relative to newer, AI-first boutiques.
HCLTech
+ Two named proprietary platforms (Graviton, AION) provide concrete, productized AI lifecycle tooling beyond generic consulting claims.
+ Multiple AWS competency certifications (networking, migration, financial services, manufacturing, DevOps) support broad technical credibility.
+ Very large scale (224,000+ employees across 60 countries) supports substantial global delivery capacity.
+ Long corporate history (roots to 1976) provides deep enterprise IT relationship experience.
- The exact founding date and scope of HCLTech's dedicated AI/ML practice specifically (versus the parent company) is not clearly documented in available public sources.
- No clearly located aggregate Clutch/G2 star rating specific to its AI/ML practice.
- Pricing model and minimum engagement are not published, and typical minimums are substantial for enterprise engagements.
- Extremely broad service portfolio means AI/ML model development competes with many other large practice areas for attention.

Who should choose ELEKS?

ELEKS is the right choice for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..

One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades.. Minimum engagement starts at Not published. Works best with clients in Financial services, Healthcare, Manufacturing, Insurance.

Who should choose HCLTech?

HCLTech is the right choice for very large enterprises wanting a full-stack AI vendor spanning hardware/chip-level work through to business process optimization..

Unusually broad "chip-to-cloud" AI stack claim backed by two named proprietary platforms (Graviton for ML development, AION for AI lifecycle management), a combination not matched by most peers in this list.. Minimum engagement starts at Not published. Works best with clients in Manufacturing, Financial services, Telecommunications, Automotive.

Decision matrix: ELEKS vs HCLTech

Your situation Recommended choice
You need full-ownership delivery on a defined project scope ELEKS
You need a large dedicated team for an ongoing programme ELEKS
Your budget is at the lower end Compare: ELEKS (Not published) vs HCLTech (Not published)
You need specialist depth in a specific vertical ELEKS
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Both may offer discovery engagements

Use case fit: ELEKS vs HCLTech

Use case ELEKS fit HCLTech fit Winner
Running an enterprise-scale data science initiative alongside a broader software modernization program Strong Limited ELEKS
Engaging a long-tenured, stable partner for a multi-year digital transformation that includes ML components Strong Limited ELEKS
Very large manufacturing or automotive enterprises needing a chip-to-cloud AI vendor Limited Strong HCLTech
Deploying generative AI solutions using Amazon Bedrock, SageMaker, and Q at enterprise scale Limited Strong HCLTech
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Limited Limited Both equally

Verdict: ELEKS vs HCLTech

ELEKS (4.1/5) is the stronger overall choice for most ML Model Development projects. One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades.. It is best for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor..

HCLTech (3.9/5) is the better choice when very large enterprises wanting a full-stack AI vendor spanning hardware/chip-level work through to business process optimization.. If your situation matches those criteria, HCLTech is a competitive option.

Related comparisons

ELEKS vs HCLTech FAQ

Is ELEKS better than HCLTech?

ELEKS (4.1/5) scores higher overall, but "better" depends on your use case. ELEKS is better for enterprises wanting a long-established European software engineering partner with an added data science practice rather than an AI-only startup vendor.. HCLTech is better for very large enterprises wanting a full-stack AI vendor spanning hardware/chip-level work through to business process optimization..

How do ELEKS and HCLTech differ in pricing?

ELEKS uses time & material, fixed project pricing with a minimum engagement of Not published. HCLTech uses not published; enterprise project engagements 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: ELEKS or HCLTech?

ELEKS 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 ELEKS and HCLTech?

ELEKS's primary differentiator is: one of the longest operating histories (since 1991) among firms researched for this list, predating the ai consulting boom by decades.. HCLTech's primary differentiator is: unusually broad "chip-to-cloud" ai stack claim backed by two named proprietary platforms (graviton for ml development, aion for ai lifecycle management), a combination not matched by most peers in this list.. They also differ in team size (1,001–5,000 vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Healthcare vs Manufacturing, Financial services).

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