Enterprise AI Platform Comparison — 2026

MAIA Brain vs Amazon Bedrock vs a Build-Your-Own Model API That Still Requires an Engineering Team.

Amazon Bedrock gives access to foundation models via API — but accessing models is not the same as having a working enterprise automation platform. European enterprises evaluating Bedrock are often discovering they still need to build, orchestrate, govern, and maintain the entire application layer themselves, from inside AWS's cloud.

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65%
Lower total cost of ownership vs building on AWS Bedrock
4–6 wks
To go live (vs 9–18+ months building on Bedrock)
Zero
AWS engineering required
100%
On-premise capable & EU AI Act ready
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What Is Amazon Bedrock — and What Is It Not?

Amazon Bedrock is a powerful managed API service giving access to leading foundation models from Anthropic, Meta, Mistral, and others — within AWS's cloud. It is not an enterprise automation platform. Organisations comparing MAIA Brain and Bedrock are typically comparing outcomes: enterprises want invoice processing, document understanding, autonomous exception handling, and process orchestration running in weeks. Bedrock can enable these outcomes — but requires building the full application, orchestration layer, governance framework, and compliance controls from scratch, on AWS cloud infrastructure, with no on-premise option. Learn more about intelligent automation or see how MAIA compares across the market in our 2026 platform comparison.

MAIA delivers enterprise AI automation in weeks — no AWS build project, no cloud lock-in, on-premise by default
Side-by-Side

MAIA Brain vs Amazon Bedrock / AWS AI — In Plain English

A direct comparison of what each platform delivers out of the box for enterprise automation teams evaluating their options in 2026.

Capability Amazon Bedrock / AWS AI MAIA Brain
Automate enterprise operations without a build project No — requires building the full application on top of the model API Yes
Run fully on-premise No — AWS cloud only; data leaves your environment Yes
Read and understand unstructured documents natively Partial — possible via model API calls but application layer must be built and maintained Yes
Handle exceptions without stopping No — exception handling must be built into every custom workflow Yes
Connect enterprise software (SAP, Salesforce, Oracle) Partial — AWS integrations available but custom orchestration required Yes — 500+ pre-built
EU AI Act and GDPR compliance from day one No — data processed on AWS cloud; EU sovereignty requires extensive architecture Yes
Business teams configure automation in plain language No — requires Python/AWS SDK engineering for all configuration Yes
Transparent, predictable pricing No — token-based consumption pricing with significant variation at scale Yes
Time to first production automation 9–18+ months of build, test, and governance before production 4–6 weeks
Onboarding and configuration included No — all build and configuration is your engineering team's responsibility Yes
Get smarter without engineering intervention No — model updates and application improvements require engineering cycles Yes
Multi-language support Yes — models support major languages Yes — native reasoning
Full audit trail and decision explainability Partial — must be built as part of the application layer Yes
Total Cost of Ownership

Significantly Less. Everything Included.

The real cost of building on Amazon Bedrock is not the model API fee — it is the engineering team, the application build, the orchestration layer, the governance framework, the AWS infrastructure, and the ongoing maintenance. MAIA delivers the business outcome without the engineering project cost.

The Hidden Cost of Building on Amazon Bedrock

AWS Bedrock's token-based API pricing is only the starting point. Before a single production automation runs, European enterprises typically need an AWS engineering team, months of application development, a custom orchestration layer, AWS infrastructure costs (Lambda, Step Functions, API Gateway, S3), custom compliance architecture, and ongoing DevOps resource. The full build cost routinely reaches seven figures before ROI is visible.

MAIA Brain — What You Get

  • Full AI automation platform — document intelligence, orchestration, exception handling included
  • Native document intelligence — reads, classifies, and extracts unstructured data from day one
  • Autonomous exception handling — completes tasks with a full audit trail, no human escalation required
  • Full on-premise deployment — your infrastructure, your data, no cloud dependency
  • 500+ enterprise connectors — SAP, Salesforce, Oracle, ServiceNow and more, pre-built
  • EU AI Act compliance built in — explainability, audit trail, and data governance as standard
  • Full onboarding by MAIA's team — no internal engineering effort required
  • No AWS engineering or DevOps required — zero cloud infrastructure management
One transparent platform fee. No token billing. No AWS infrastructure costs. No surprise invoices.

Amazon Bedrock — What You Must Build

  • AWS/Bedrock engineering team to build the application layer on top of the model API
  • Model orchestration and prompt engineering development — maintained and versioned by your team
  • AWS infrastructure setup — Lambda, API Gateway, Step Functions, S3, IAM, CloudWatch
  • AWS Bedrock token-based consumption costs — variable, difficult to forecast at enterprise scale
  • Custom EU compliance and audit trail development — not provided by Bedrock as a service
  • Ongoing model monitoring, versioning, and retraining — engineering resource required throughout
  • AWS SageMaker and additional service costs for production-grade pipelines and evaluation
  • Security and access control architecture build — IAM policies, VPC configuration, data encryption

Cost comparison based on representative enterprise automation scenarios. Total cost of ownership analysis available on request. Individual results will vary based on organisational complexity, existing AWS infrastructure, and automation scope.

Platform Capabilities

Why MAIA Brain Is Not a Bedrock Wrapper

Six structural differences that determine whether you are buying an automation platform or commissioning a build project.

Running on Day One

Bedrock is an API. MAIA is a running automation platform. No build required, no model to orchestrate, no application to architect. Your first production automation is live within 4–6 weeks of onboarding.

No build project
Bedrock alternative: 9–18+ months of engineering before production

True On-Premise Deployment

Bedrock requires AWS cloud. MAIA runs on your infrastructure. For EU AI Act and GDPR, this is a structural difference, not a configuration option. Your data never enters AWS or any third-party cloud environment.

Data sovereignty guaranteed
Bedrock alternative: All data processed on AWS cloud — no on-premise option exists

No AWS Engineering Required

Building on Bedrock requires Python, AWS SDK, Lambda, and DevOps expertise. MAIA's team manages onboarding and configuration. Your operations team runs the platform in plain language — no AWS certifications needed.

Operations-team ready
Bedrock alternative: Deep AWS expertise required across the full engineering lifecycle

Autonomous Exception Handling

Custom Bedrock applications need exception handling coded into every workflow. MAIA reasons through exceptions natively — completing tasks with a full audit trail, no human escalation required, even for complex edge cases.

Self-resolving workflows
Bedrock alternative: Every exception scenario requires custom engineering to handle

Predictable Pricing Without AWS Bills

Bedrock's token-based consumption pricing is difficult to forecast at enterprise scale. MAIA's pricing is transparent and fixed — no surprise cloud bills, no per-token costs, no AWS infrastructure invoices to manage each month.

Fixed, transparent pricing
Bedrock alternative: Variable consumption billing plus AWS infrastructure costs at scale

EU AI Act Compliance by Design

Building EU AI Act compliance on Bedrock requires custom explainability, audit trail, and data governance engineering. MAIA includes all of these as standard. Learn more about MAIA's AI security and compliance capabilities.

Compliant from day one
Bedrock alternative: Custom compliance architecture required — significant engineering investment
How It Works

From Evaluation to Live Automation — Without the AWS Build

Three steps from first conversation to production automation. No AWS infrastructure provisioning, no engineering sprints, no model orchestration.

01

Automation Discovery

MAIA's team works with your operations and finance teams to identify the highest-value automation opportunities — invoice processing, claims handling, exception management, data reconciliation. No AWS architecture knowledge required from your side.

02

Platform Configuration & On-Premise Deployment

MAIA deploys to your own infrastructure — no AWS account required, no cloud data transfer. The platform connects to your enterprise systems via pre-built connectors for SAP, Salesforce, Oracle and others. Configuration is managed by MAIA's team, not your IT department.

03

Live Automation in Weeks

Within 4–6 weeks, your first production automation is processing real documents, handling real exceptions, and generating real audit trails — on your infrastructure, under your control, fully EU AI Act compliant. No 9-month AWS engineering project, no consumption bills, no cloud vendor dependency.

Which Platform Is Right?

An Honest Assessment — Choose the Right Tool

Not every enterprise needs MAIA. For organisations comparing broader options, see also our comparisons of MAIA vs Blue Prism and MAIA vs Google Vertex AI.

Consider Bedrock If...

  • Your engineering team is deeply experienced in AWS and wants to build custom AI applications from the ground up
  • You need fine-grained control over model selection, prompting strategies, and response handling at a technical level
  • Your workloads are too specialised or novel for an off-the-shelf enterprise automation platform
  • Cloud-first AWS infrastructure is your company-wide strategy and all data processing in AWS cloud is acceptable
  • You have the engineering resource, timeline, and budget for a significant multi-month build project before production

MAIA Brain Is Likely the Better Fit If...

  • You need enterprise automation running in weeks without commissioning an engineering build project
  • EU data sovereignty requires data to stay on your own infrastructure, not AWS cloud — a legal or regulatory requirement
  • Your operations team needs to configure and manage processes without AWS SDK or Python engineering expertise
  • You need predictable, transparent pricing without per-token consumption costs and variable AWS infrastructure billing
  • Document-heavy processes need intelligent automation from day one, not after months of model orchestration engineering
  • Built-in EU AI Act compliance is a regulatory requirement, not a post-launch engineering project
From the Field
"
★★★★★

We spent three months scoping a build on Amazon Bedrock before concluding that we were commissioning a 14-month engineering project, not buying an automation platform. MAIA Brain was our alternative evaluation — and within six weeks it was live, fully on-premise, processing our insurance claims documentation without any AWS infrastructure, any engineering team, or any cloud data risk. The operational comparison was not even close.

COO
Chief Operations Officer
European Insurance Group (Representative scenario)
Platform Standards
Common Questions

MAIA Brain vs Amazon Bedrock — FAQ

Answers to the questions enterprises most commonly ask when evaluating MAIA Brain against Amazon Bedrock or AWS AI services.

In total cost of ownership terms, yes — significantly. Amazon Bedrock's model API fees are only one component of the cost. Building on Bedrock requires an engineering team to develop the application layer, orchestration framework, AWS infrastructure, security architecture, compliance controls, and ongoing maintenance. MAIA Brain delivers a complete enterprise automation platform for a transparent, predictable fee with no engineering build cost, no AWS infrastructure cost, and no consumption-based surprise billing. Organisations typically see up to 65% lower total cost of ownership versus building on Bedrock.
Yes. MAIA Brain is designed for full on-premise deployment. All AI processing, document understanding, and automation orchestration runs on your own infrastructure — your data never leaves your environment. Amazon Bedrock is a cloud-only service; data is processed on AWS infrastructure, which creates data sovereignty and EU AI Act compliance challenges for European enterprises. This is a structural architectural difference, not a configuration option.
Amazon Bedrock is a managed API service that provides access to foundation models from providers including Anthropic, Meta, Mistral, and others. It gives you model access — it does not give you an automation platform. To automate enterprise operations on Bedrock, your team must build the entire application layer: prompt engineering, orchestration logic, exception handling, enterprise system connectors, compliance controls, audit trails, and monitoring. MAIA Brain is a complete enterprise AI automation platform — document intelligence, process orchestration, exception handling, 500+ enterprise connectors, and EU AI Act compliance are all included and running from day one.
MAIA Brain includes native document intelligence — it reads, understands, classifies, and extracts data from unstructured documents (invoices, contracts, claims forms, purchase orders) without custom development. On Amazon Bedrock, document processing is possible but must be engineered: your team must build document ingestion pipelines, design prompts for extraction, handle format variation, manage errors, and maintain the application as documents change. MAIA's document intelligence is operational from the first week; a comparable Bedrock implementation typically requires months of engineering.
No. MAIA Brain requires no AWS knowledge, no cloud engineering, and no DevOps capability. MAIA's team manages onboarding, configuration, and integration. Your operations team manages processes using plain-language configuration. Amazon Bedrock requires deep AWS expertise — Python development, AWS SDK, Lambda, API Gateway, Step Functions, IAM, and CloudWatch are all typically required to build a production automation application on Bedrock.
MAIA Brain's onboarding team handles the full implementation. If your organisation has been scoping or prototyping on Bedrock, MAIA's team will assess your automation requirements and configure the platform to match them — typically delivering the first production automation within 4–6 weeks. There is no AWS migration complexity: MAIA deploys to your own infrastructure and connects to your enterprise systems directly. Existing Bedrock prototypes or proof-of-concept work can inform the MAIA configuration, but there is no technical dependency on AWS for the transition.
Get Started

Skip the Build. Start the Automation. Enterprise AI Running in 4–6 Weeks.

Building on Amazon Bedrock is a 12–18 month engineering project before your first production automation. MAIA Brain is live in 4–6 weeks, on your infrastructure, with no AWS build, no consumption billing surprises.

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On-Premise No Build Required EU AI Act Ready Weeks Not Months