Top AI Integration Services

Neurons Lab vs EPAM Systems: full comparison for 2026

Quick verdict

Neurons Lab (4.5/5) edges ahead of EPAM Systems (4.1/5) overall. Neurons Lab is the better choice for banks and insurers piloting AI agents. EPAM Systems is the stronger option for enterprises with multi-year engineering budgets. The right choice depends on your project size, budget, and required tech stack.

Neurons Lab vs EPAM Systems: head-to-head summary

Criterion Neurons Lab EPAM Systems
Founded 2019 1993
HQ London, UK Newtown, PA, USA
Team size 50–249 61,000+
Rating 4.5 / 5 4.1 / 5
Primary differentiator AWS Generative AI competency combined with a financial-services client base Engineering capacity across Europe, India, and the Americas for long AI programs
Pricing model Fixed-scope discovery and pilots, then time & materials; rates on request Time & materials and dedicated teams; rates on request
Min. engagement Not disclosed Not disclosed
Primary tech stack AWS Bedrock, Amazon SageMaker, LangChain Azure OpenAI, AWS Bedrock, Databricks
Industries served Financial services, Insurance, Healthcare Financial services, Healthcare, Retail & e-commerce, Media, Energy

Neurons Lab vs EPAM Systems: overview

Neurons Lab

Founded in 2019 and based in London with a second office in Singapore, Neurons Lab is a small AI consultancy of roughly 50–250 people that draws on a wider contractor network. In March 2024 it became one of the first firms to earn the AWS Generative AI competency, and it's an AWS Advanced Tier partner. Its work skews toward banks and insurers that want agents running inside existing compliance controls; HSBC and Visa appear as named clients in third-party listings (independently unverifiable). The firm is smaller than most of this list, but its regulated-industry experience is unusually concentrated for its size.

EPAM Systems

EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with over 61,200 employees at the end of 2025. Acquisitions shaped the recent mix: NEORIS (2024) for Latin America and Iberia, and First Derivative (completed December 2024) for financial-services data. Management targets more than $600 million of AI-native revenue in 2026, after reporting over $105 million in Q4 2025. Its AI/Run tooling and Agentic QA product support large engineering programs more than single-workflow pilots.

Services and capabilities: Neurons Lab vs EPAM Systems

Capability Neurons Lab EPAM Systems
CRM / ERP integration ✗ ✓
LLM API gateway & cost control ✓ ✓
Document processing ✗ ✗
Conversational AI ✓ ✗
Agentic workflows ✓ ✓
Fixed-price pilot ✗ ✗
Managed services after launch ✗ ✓

Tech stack comparison: Neurons Lab vs EPAM Systems

Framework / platform Neurons Lab EPAM Systems
Salesforce ✓ N/A
SAP N/A ✓
Microsoft Dynamics 365 N/A N/A
HubSpot N/A N/A
Snowflake N/A ✓
Databricks N/A ✓
BigQuery N/A N/A
Azure OpenAI N/A ✓
AWS Bedrock ✓ ✓
Zendesk N/A N/A

Pricing comparison: Neurons Lab vs EPAM Systems

Criterion Neurons Lab EPAM Systems
Minimum engagement Not disclosed Not disclosed
Engagement models Fixed-scope project, Time & materials Time & materials, Dedicated team, Managed services
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Neurons Lab vs EPAM Systems

Dimension Neurons Lab EPAM Systems
Best company size Startup to mid-market Enterprise
Best industries Financial services, Insurance, Healthcare Financial services, Healthcare, Retail & e-commerce
Best use cases An agent that prepares KYC (know your customer) case files for an analyst to approve, Claims triage assistants that read policy documents Large data-platform programs that end in AI features, Agent development across several business units
Typical project type Fixed-scope project Time & materials

Neurons Lab vs EPAM Systems: pros and cons

Neurons Lab
+ Among the earliest holders of the AWS Generative AI competency, announced March 2024.
+ Most case work comes from banking and insurance, where audit trails and approvals are part of the spec.
+ Senior consultants run delivery directly on a team this size.
+ AWS Public Sector Partner status since September 2024 opens government procurement routes.
- Its client work is concentrated in finance, so references in manufacturing or retail are thin
- Headcount figures conflict between sources, and part of the bench is contracted
- No managed-service option is described for after go-live
EPAM Systems
+ Engineering depth to staff many workstreams at once.
+ Public reporting on AI-native revenue gives a measurable view of the practice.
+ First Derivative added capital-markets data skills.
+ Agentic QA product addresses testing of AI-generated code.
- Acquisition-driven growth (NEORIS, First Derivative) means teams are still being integrated
- Not built for a small fixed-price pilot
- Management flagged slower organic growth in 2026 guidance

Who should choose Neurons Lab?

A typical fit: an agent that prepares KYC (know your customer) case files for an analyst to approve.

AWS Generative AI competency combined with a financial-services client base. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Insurance, Healthcare.

Who should choose EPAM Systems?

A typical fit: large data-platform programs that end in AI features.

Engineering capacity across Europe, India, and the Americas for long AI programs. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Media, Energy.

Decision matrix: Neurons Lab vs EPAM Systems

Your situation Recommended choice
You want a priced pilot before committing to a rollout Neither advertises one; ask for a scoped pilot quote
You need someone to run and monitor the system after launch EPAM Systems
Your budget is at the lower end Compare: Neurons Lab (Not disclosed) vs EPAM Systems (Not disclosed)
The AI has to read and write in your CRM or ERP EPAM Systems
You need multi-step agents acting across systems Both build agentic workflows
You need a large team for a multi-year program EPAM Systems

Use case fit: Neurons Lab vs EPAM Systems

Use case Neurons Lab fit EPAM Systems fit Winner
An agent that prepares KYC (know your customer) case files for an analyst to approve Strong Limited Neurons Lab
Claims triage assistants that read policy documents Strong Limited Neurons Lab
Large data-platform programs that end in AI features Limited Strong EPAM Systems
Agent development across several business units Limited Strong EPAM Systems

Verdict: Neurons Lab vs EPAM Systems

Neurons Lab (4.5/5) is the stronger overall choice for most AI Integration Services projects. AWS Generative AI competency combined with a financial-services client base.

EPAM Systems (4.1/5) is worth a look if you need agent development across several business units. If your situation matches that, EPAM Systems is a competitive option.

Related comparisons

Neurons Lab vs EPAM Systems FAQ

Is Neurons Lab better than EPAM Systems?

Neurons Lab (4.5/5) scores higher overall, but "better" depends on your use case. Neurons Lab's strongest advantage: among the earliest holders of the AWS Generative AI competency, announced March 2024. EPAM Systems's strongest advantage: engineering depth to staff many workstreams at once.

How do Neurons Lab and EPAM Systems differ in pricing?

Neurons Lab's pricing: fixed-scope discovery and pilots, then time & materials; rates on request. EPAM Systems's pricing: time & materials and dedicated teams; rates on request. Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.

Which is better for enterprise: Neurons Lab or EPAM Systems?

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

What are the main differences between Neurons Lab and EPAM Systems?

Neurons Lab's primary differentiator is: AWS Generative AI competency combined with a financial-services client base. EPAM Systems's primary differentiator is: engineering capacity across Europe, India, and the Americas for long AI programs. They also differ in team size (50–249 vs 61,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Insurance vs Financial services, Healthcare).

Verify all details directly with each provider before making a decision.