Best Machine Learning Agencies

Centric Consulting vs Modak: full comparison for 2026

Last updated: July 2026

Quick verdict

Centric Consulting (3.7/5) edges ahead of Modak (3.7/5) overall. Centric Consulting is the better choice for uS mid-to-large enterprises needing ML consulting integrated within business strategy and management transformation. Modak is the stronger option for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption. The right choice depends on your project size, budget, and required tech stack.

Centric Consulting vs Modak: head-to-head summary

Criterion Centric Consulting Modak
Founded 1999 2016
HQ Columbus, OH San Jose, CA
Team size 800+ 100–200
Rating 3.7 / 5 3.7 / 5
Best for US mid-to-large enterprises needing ML consulting integrated within business strategy and management transformation Large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption
Pricing model T&M, retainer T&M, retainer
Min. engagement $50K+ $50K+
Primary tech stack Python, Azure, AWS Python, Apache Spark, Databricks
Industries served financial, healthcare, manufacturing, retail, logistics financial, healthcare, manufacturing, logistics, saas

Centric Consulting vs Modak: overview

Centric Consulting

Centric Consulting is a US-based management consulting firm with 25 years of experience, headquartered in Columbus, Ohio, with 800+ professionals. The company provides AI strategy, ML consulting, cloud solutions, and cyber risk management, positioning ML as a tool for business forecasting, fraud detection, and process optimisation within broader transformation programmes. (Founding year and scale per Centric Consulting official website.)

Modak

Modak is an AI-native data engineering company headquartered in San Jose, California, founded in 2016. The company uses machine learning techniques to transform how structured and unstructured enterprise data is prepared, consumed, and shared — focusing on AI-driven data modernisation for large organisations. Global consulting services help enterprises modernise data infrastructure, accelerate AI readiness, and drive measurable business outcomes. (Founding year and approach per Modak official website and ZoomInfo.)

Services and capabilities: Centric Consulting vs Modak

Capability Centric Consulting Modak
Custom ML build
ML consulting
Computer vision
NLP / LLM
Predictive analytics
MLOps
Data engineering
Generative AI
Staff augmentation
Fixed-price projects
Dedicated team model

Tech stack comparison: Centric Consulting vs Modak

Framework / platform Centric Consulting Modak
Python
TensorFlow N/A N/A
PyTorch N/A N/A
AWS SageMaker N/A N/A
Azure ML N/A N/A

Pricing comparison: Centric Consulting vs Modak

Criterion Centric Consulting Modak
Minimum engagement $50K+ $50K+
Engagement models T&M, Retainer T&M, Retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Centric Consulting vs Modak

Dimension Centric Consulting Modak
Best company size Startup to mid-market Startup to mid-market
Best industries financial, healthcare, manufacturing financial, healthcare, manufacturing
Best use cases ML strategy within business transformation, Forecasting model for manufacturing operations Enterprise data modernisation for AI readiness, ML-powered ETL and data prep pipeline
Typical project type T&M T&M

Centric Consulting vs Modak: pros and cons

Centric Consulting
+ 25 years of US management consulting experience — strong business context
+ ML integrated within broader transformation programme delivery
+ Multiple US locations — accessible for on-site engagement
+ Azure and cloud expertise alongside ML consulting
- ML is an ancillary offering within management consulting — not ML-first
- Higher overhead than boutique ML agencies — pricing reflects consulting firm structure
- Less suited to pure technical ML builds or data engineering
Modak
+ ML applied to data engineering itself — accelerates data prep for ML programmes
+ AI-native from inception — not a repositioned data warehouse firm
+ Strong on unstructured data processing for AI readiness
+ San Jose HQ with enterprise client focus
- Data engineering focus — not suited to custom ML model development or computer vision
- Minimum engagement oriented toward large enterprise programmes
- Less suited to companies without an existing large data estate

Who should choose Centric Consulting?

Centric Consulting is the right choice for uS mid-to-large enterprises needing ML consulting integrated within business strategy and management transformation.

Business-outcome ML consulting — AI within management transformation, not pure technology delivery. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, manufacturing, retail, logistics.

Who should choose Modak?

Modak is the right choice for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.

ML-powered data engineering — uses ML itself to accelerate data prep and modernisation at enterprise scale. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, manufacturing, logistics, saas.

Decision matrix: Centric Consulting vs Modak

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Both offer fixed-price models
You need a large dedicated team for an ongoing programme Check each company's engagement model
Your budget is at the lower end Centric Consulting
You need specialist depth in a specific vertical Centric Consulting
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Centric Consulting

Use case fit: Centric Consulting vs Modak

Use case Centric Consulting fit Modak fit Winner
ML strategy within business transformation Strong Strong Both equally
Forecasting model for manufacturing operations Strong Limited Centric Consulting
Enterprise data modernisation for AI readiness Strong Strong Both equally
ML-powered ETL and data prep pipeline Limited Strong Modak
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Centric Consulting vs Modak

Centric Consulting (3.7/5) is the stronger overall choice for most Machine Learning projects. Business-outcome ML consulting — AI within management transformation, not pure technology delivery. It is best for uS mid-to-large enterprises needing ML consulting integrated within business strategy and management transformation.

Modak (3.7/5) is the better choice when large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption. If your situation matches those criteria, Modak is a competitive option.

Related comparisons

Centric Consulting vs Modak FAQ

Is Centric Consulting better than Modak?

Centric Consulting (3.7/5) scores higher overall, but "better" depends on your use case. Centric Consulting is better for uS mid-to-large enterprises needing ML consulting integrated within business strategy and management transformation. Modak is better for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.

How do Centric Consulting and Modak differ in pricing?

Centric Consulting uses t&m, retainer pricing with a minimum engagement of $50K+. Modak uses t&m, retainer pricing with a minimum engagement of $50K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Centric Consulting or Modak?

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

What are the main differences between Centric Consulting and Modak?

Centric Consulting's primary differentiator is: business-outcome ml consulting — ai within management transformation, not pure technology delivery. Modak's primary differentiator is: ml-powered data engineering — uses ml itself to accelerate data prep and modernisation at enterprise scale. They also differ in team size (800+ vs 100–200), minimum engagement ($50K+ vs $50K+), and primary industries served (financial, healthcare vs financial, healthcare).

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