Build in weeks. Not years.

Custom AI Agents that deliver real ROI

Custom AI Agents that deliver real ROI

We're the AI-Native Systems Integrator that deploys AI agents into your workflows, delivering value while old-school consultants are still designing proposal slides.

Not your traditional systems integrator

A.Team is rewriting the traditional systems integrator and consulting playbook for insane efficiency, speed, and risk mitigation.

AI Implementation Challenges

A.Team Approach

Black Box Processes

Critical AI components like embedding calculations and chunking methods lack transparency and tunability, making systematic optimization nearly impossible.

Deterministic Workflows

Our engineers build evaluable, tunable data pipelines that maintain high accuracy across every step, achieving the 95%+ reliability critical applications demand.

Compounding Errors

Each RAG pipeline step introduces errors that multiply, reducing 90% accurate components to 60-80% overall accuracy—far below what critical applications require.

Continuous Improvement

Our implementation includes built-in feedback loops and measurement systems that ensure your AI solutions get better over time, not stale.

See more

AI Implementation Challenges

A.Team Approach

Black Box Processes

Critical AI components like embedding calculations and chunking methods lack transparency and tunability, making systematic optimization nearly impossible.

Deterministic Workflows

Our engineers build evaluable, tunable data pipelines that maintain high accuracy across every step, achieving the 95%+ reliability critical applications demand.

Compounding Errors

Each RAG pipeline step introduces errors that multiply, reducing 90% accurate components to 60-80% overall accuracy—far below what critical applications require.

Continuous Improvement

Our implementation includes built-in feedback loops and measurement systems that ensure your AI solutions get better over time, not stale.

See more

AI Implementation Challenges

A.Team Approach

Black Box Processes

Critical AI components like embedding calculations and chunking methods lack transparency and tunability, making systematic optimization nearly impossible.

Deterministic Workflows

Our engineers build evaluable, tunable data pipelines that maintain high accuracy across every step, achieving the 95%+ reliability critical applications demand.

Compounding Errors

Each RAG pipeline step introduces errors that multiply, reducing 90% accurate components to 60-80% overall accuracy—far below what critical applications require.

Continuous Improvement

Our implementation includes built-in feedback loops and measurement systems that ensure your AI solutions get better over time, not stale.

See more

The Challenges

The A.Team Approach

AI implementation challenges

Black Box Processes

Critical AI components like embedding calculations and chunking methods lack transparency and tunability, making systematic optimization nearly impossible.

Compounding Errors

Each RAG pipeline step introduces errors that multiply, reducing 90% accurate components to 60-80% overall accuracy—far below what critical applications require.

Data Quality Gap

Most business data exists in unstructured formats requiring sophisticated processing before AI can extract meaningful insights.

Talent Bottle Neck

67% of leaders cite AI skills gaps as their primary adoption barrier, delaying critical initiatives and limiting potential impact.

Foundation Failures

78% of organizations lack the data infrastructure necessary for successful GenAI implementation, building on unstable foundations.

Time-to-Value Delays

Traditional AI implementations require 12+ months of development and deployment, delaying ROI and giving competitors time to move ahead.

Measurement Blindness

Without KPIs for AI performance (missing in 62% of organizations), teams can't demonstrate ROI or systematically improve results.

Integration Complexity

Off-the-shelf solutions rarely connect seamlessly with your unique data and workflows, creating friction that kills adoption.

The Challenges

The A.Team Approach

AI implementation challenges

Black Box Processes

Critical AI components like embedding calculations and chunking methods lack transparency and tunability, making systematic optimization nearly impossible.

Compounding Errors

Each RAG pipeline step introduces errors that multiply, reducing 90% accurate components to 60-80% overall accuracy—far below what critical applications require.

Data Quality Gap

Most business data exists in unstructured formats requiring sophisticated processing before AI can extract meaningful insights.

Talent Bottle Neck

67% of leaders cite AI skills gaps as their primary adoption barrier, delaying critical initiatives and limiting potential impact.

Foundation Failures

78% of organizations lack the data infrastructure necessary for successful GenAI implementation, building on unstable foundations.

Time-to-Value Delays

Traditional AI implementations require 12+ months of development and deployment, delaying ROI and giving competitors time to move ahead.

Measurement Blindness

Without KPIs for AI performance (missing in 62% of organizations), teams can't demonstrate ROI or systematically improve results.

Integration Complexity

Off-the-shelf solutions rarely connect seamlessly with your unique data and workflows, creating friction that kills adoption.

Agents customized to your use case

A.Team has helped clients launch multi-model AI systems supporting millions of users in as little as 16 weeks. Partner with us to build custom AI Agents for your specific use case.

A proven approach to launching faster

A proven approach to launching faster

Design & agentic framework

~2 weeks

Problem definition

Establish success metrics & benchmarks

Set up secure data pipelines & AI Control Room

Identify relevant vendors/technologies

Expertise

AI Architect, Product

Solution development (sprints)

~3 months

Execute in iterative sprints with teams scaled according to each phase

Deliver working solution

Allow for scope expansion

Expertise

AI Architect, Product, Data Engineer, ML Engineer, UX Designer

Monitor & optimize

Ongoing

Maintain performance

Further model tuning

Integrate new data sources

Keep infrastructure up-to-date

Expertise

MLOps, ML Engineer

The build vs. buy equation is no longer relevant

Differentiated value comes from flexible approaches that activate your data and customize the last mile. A.Team’s Assemble approach combines the best available tools with customization where it matters.

A.Team helped Accrue Savings reinvent buy now pay later system that raised $30M.

A.Team helped Accrue Savings reinvent buy now pay later system that raised $30M.

A.Team helped Accrue Savings reinvent buy now pay later system that raised $30M.

8 experts

deployed on the project

deployed on the project

70%

boost in conversion

boost in conversion

A.Team assembled a specialized fintech team and within a 100 days built a market-ready solution that proved the viability of this revolutionary concept with major retailers.

A.Team assembled a specialized fintech team and within a 100 days built a market-ready solution that proved the viability of this revolutionary concept with major retailers.

Read the case study ->

How we built D-ID’s award-winning AI animation tool that reached a million users and raised $48M.

24 experts deployed

24 experts deployed

150M+ videos created

150M+ videos created

A.Team assembled and seamlessly integrated expert mobile developers with D-ID's team, facilitating the rapid development and launch of an MVP in just five months.

Read the case study ->

A.Team helped Inflection speed up the development of their innovative AI assistant MVP that raised $1.3B.

8 experts deployed

8 experts deployed

$4B valuation

$4B valuation

Inflection has augmented their team with expert data engineers and full-stack developers to build robust pipelines for their innovative AI products in order to go to market faster.

Read the case study ->

A.Team partnered with Lettuce to develop an AI powered financial platform that makes finance easy for solopreneurs.

5 experts deployed

5 experts deployed

$6M raised post project

$6M raised post project

A.Team's experts shaped and built the product in just 6 months. The collaborative effort resulted in a user-friendly interface, enabling hassle-free management of financial and legal tasks.

Read the case study ->

After the platform rebuild Apprentice became one of the healthcare industry’s most promising startups that raised a $100M.

50 experts placed

50 experts placed

38x return of investment

38x return of investment

A.Team experts integrated with Apprentice’s core tech team, working from within their organization to ramp up efficiency. This allowed Apprentice to build a new version of their platform within just 45 days. 

Read the case study ->

Approach

Build Approach

Build

A.Team Assemble

Buy

Time to market

12+ months

12+ months

2-3 month iterations

3-6 months

Cost

High ($MM) + maintenance

High cost ($MM) + maintenance

Flexible, pay-for-what-you-use

High vendor costs

Customization

✅ Yes, but extensive effort

✅ Customizable, but extensive effort

✅ Yes, but accelerated

❌ Limited, often siloed

Risk

❌ Requires heavy infrastructure

❌ Requires heavy infrastructure

✅ No lock-in, modular AI stack

❌ Vendor lock-in, external roadmap

AI Expertise

❌ In-house teams required

❌ In-house teams required

✅ Elite AI experts, immediate start

❌ Generic implementation

Buy Approach

3-6 months

High vendor costs

❌ Limited, often siloed

❌ Vendor lock-in, external roadmap

❌ Generic implementation

A.Team Assemble

2-3 month iterations

Flexible, pay-for-what-you-use

✅ Yes, but accelerated

✅ No lock-in, modular AI stack

✅ Elite AI experts, immediate start

Providers and integrations

You probably have questions
We have answers

You probably have questions
We have answers

You probably have questions
We have answers

How do you measure ROI for AI agents?

How do you measure ROI for AI agents?

How do you measure ROI for AI agents?

How do you measure ROI for AI agents?

What happens after implementation?

What happens after implementation?

What happens after implementation?

What happens after implementation?

How do you handle data privacy and security?

How do you handle data privacy and security?

How do you handle data privacy and security?

How do you handle data privacy and security?

What makes your approach different from traditional consultants?

What makes your approach different from traditional consultants?

What makes your approach different from traditional consultants?

What makes your approach different from traditional consultants?

What types of integration are possible?

What types of integration are possible?

What types of integration are possible?

What types of integration are possible?

How much technical knowledge do we need to have?

How much technical knowledge do we need to have?

How much technical knowledge do we need to have?

How much technical knowledge do we need to have?

What happens if our scope changes?

What happens if our scope changes?

What happens if our scope changes?

What happens if our scope changes?

How do you handle model updates and improvements?

How do you handle model updates and improvements?

How do you handle model updates and improvements?

How do you handle model updates and improvements?

What's your approach to model fine-tuning and training?

What's your approach to model fine-tuning and training?

What's your approach to model fine-tuning and training?

What's your approach to model fine-tuning and training?

Go from POC to real ROI

Book a consultation with one of our AI Architects to discuss how custom AI Agents can transform your business operations.

Book a Consultation

Go from POC to real ROI

Book a consultation with one of our AI Architects to discuss how custom AI Agents can transform your business operations.

Book a Consultation

Go from POC to real ROI

Book a consultation with one of our AI Architects to discuss how custom AI Agents can transform your business operations.

Book a Consultation

Go from POC to real ROI

Book a consultation with one of our AI Architects to discuss how custom AI Agents can transform your business operations.

Book a Consultation

New York

Tel Aviv

© 2025 ATeams Inc., All rights reserved. Terms of Service | Privacy Policy

New York

Tel Aviv

© 2025 ATeams Inc., All rights reserved. Terms of Service | Privacy Policy

New York

Tel Aviv

© 2025 ATeams Inc., All rights reserved. Terms of Service | Privacy Policy

New York

Tel Aviv

© 2025 ATeams Inc., All rights reserved. Terms of Service | Privacy Policy