AI Pod Services

Build and launch your first AI system in weeks.

Name: AI Pod
Brand: tkxel
Rating: 4.9 (463 reviews)

6 weeks to production. Up to 70% less manual work.tkxel AI Pod combines AI architects, engineers, and product designers to build production-ready AI systems that move beyond pilots and into real workflows.

Our clients

AI pilots are easy. Production AI is where most teams get stuck.

AI is being tested, but ROI is unclear

Many businesses experiment with AI, but few can connect it to measurable business outcomes that justify further investment.

Internal teams do not have the capacity to build AI

Technology teams are already focused on product roadmaps, customer requests, and operational priorities, leaving little bandwidth for AI delivery.

AI pilots never reach real workflows

Proofs of concept often demonstrate potential but never become part of the day-to-day systems and processes employees actually use.

The scope gets too big too fast

Broad scope, disconnected data, and competing priorities can turn promising ideas into long-running projects with limited business impact.

What is an AI Pod?

AI Pod

Senior-led delivery team

A focused team of AI architects, engineers, and specialists owns the build from scope to handoff.

AI Pod

AI agents accelerate the build

Agents handle coding, testing, and evals. Engineers own decisions and integrations.

AI Pod

KPI defined before build starts

Success is agreed upfront. If we cannot measure it, we do not build it.

AI Pod

Fixed cost

One use case, one agreed cost. No open-ended time-and-materials billing, so you know the investment before the team starts building.

AI Pod

Production-ready in weeks

Your first production system is delivered in 4–6 weeks, without long discovery or stalled pilots.

AI Pod

Built to keep delivering

One Pod is not a one-off. Once the first system ships, the next use case is scoped and ready to build.

Meet the Pod

Lead AI Architect

1 per Pod, 8+ years engineering, 3+ years shipping LLM systems in production. Owns technical scope, system design, and delivery accountability from day one to handoff. Every sprint.

AI Engineers

1–2 per Pod, 5+ years engineering, 2+ years building agents, RAG pipelines, and production integrations. Handles the full build including prompts, evals, APIs, and workflow connections. Every sprint.

Product Designer

1 per Pod, included when the use case is product-shaped: copilots, assistants, or in-product AI surfaces. Owns UX, interaction design, and user-facing output quality. On demand.

Specialist Streams

Scoped per sprint, Data engineers, MLOps engineers, security specialists, and domain experts are brought in when the use case requires them. Not a fixed cost on every Pod. On demand.

How an AI Pod runs

01

01 Scope and Fit:

We identify the highest-value use case, validate feasibility, define the KPI, and lock scope before development begins.

Key deliverables: Use case brief, feasibility confirmation, KPI definition, delivery plan.

Timeline: 2–3 days

02 Build & Validate

The Pod designs, develops, tests, and validates the AI system. AI agents support coding, testing, documentation, and evaluation, while senior engineers provide oversight, own architecture and quality, and make all key decisions.

Key deliverables: Working AI system, integration-ready build, documented architecture.

Timeline: Week 1-4

03 Production Launch

The system is connected to your tools, data, and workflows so real users can begin using it in a controlled production environment.

Key deliverables: Production deployment, workflow integration, access and permissions setup.

Timeline: Week 5

04 Measure and Hand Off

We measure performance against the agreed KPI, train your team, document the solution, and hand off everything needed to operate and scale it independently.

Key deliverables: KPI results, documentation, training, operational handoff.

Timeline: Week 6

How an AI Pod runs

step 1

Scope and Fit:

We identify the highest-value use case, validate feasibility, define the KPI, and lock scope before development begins.

Key deliverables: Use case brief, feasibility confirmation, KPI definition, delivery plan.

Timeline: 2–3 days

step 2

Build & Validate

Key deliverables: Working AI system, integration-ready build, documented architecture.

Timeline: Week 1-4

step 3

Production Launch

The system is connected to your tools, data, and workflows so real users can begin using it in a controlled production environment.

Key deliverables: Production deployment, workflow integration, access and permissions setup.

Timeline: Week 5

step 4

Measure and Hand Off

We measure performance against the agreed KPI, train your team, document the solution, and hand off everything needed to operate and scale it independently.

Key deliverables: KPI results, documentation, training, operational handoff.

Timeline: Week 6

Get a free AI agent
discovery sprint.

A discovery sprint typically costs $13,800+.

Limited slots available.

17 of 25 free sprints filled.

8 remaining.

Success Stories in Spotlight

50% faster discovery with an AI-powered knowledge sharing agent

AgricultureArtificial Intelligence

View case study

"I’m going over testing feedback about the chatbot; overall, testers found the product to be fantastic. We’re very happy with this."

Chris Head

Director of IT, CCOF

GreenGro cuts support time in half with AI knowledge agent

AgricultureArtificial Intelligence

View case study

"tkxel built an AI assistant that delivers accurate guidance fast and reduces manual work."

Director of Operations

Cut customer response times by 68% through a conversational AI agent integrated with CRM systems.

SaaS & TechnologyAgentic AI

AI Support & Experience Agent

“Our support team’s workload dropped dramatically. Tkxel built an agent that responds accurately, understands context, and improves itself over time.”

Head of Customer Experience, Growing Retail Brand

Improved forecasting accuracy by 42% using a decision-intelligence agent analyzing real-time business data.

SaaS & TechnologyAgentic AI

Predictive & Decision Intelligence Agent

“We moved from reactive decisions to predictive control. Tkxel’s agent gave us visibility we never had before.”

VP Operations, Regional Logistics Network

We’ve been recognized by the best, year after year

AMERICA’S FASTEST GROWING COMPANY

TOP 100 INSPIRING WORKPLACES 2025

FORBES COACHES COUNCIL

FINANCIAL TIMES

mogul people leader

ISO 27001 CERTIFIED

ISO 20000 CERTIFIED

ISO 9001 CERTIFIED

CMMI DEV 3 CERTIFIED

Production-ready AI in as little as 6 weeks. Let’s scope yours.

“tkxel completely transformed the way we manage our customer relationships. Their customized CRM system streamlined our processes and improved customer satisfaction. We highly recommend their services to any business looking for real results.”

Nick Drogo

Global Director IT, Knowles

“They helped us build a docketing app with an intuitive user interface, allowing our attorneys to track over 10,000 U.S. and international patent systems.”

Robert K Burger

COO, Sterne Kessler

“Tkxel has proven beyond par that they excel not just in building and integrating with our team but building at a level that is at par with any US development team. Working with Tkxel is one of the best decisions we have made.”

Umair Bashir

CTO, Replenium

“tkxel shared our vision right from the get go, and helped us achieve the unthinkable through perseverance and a thorough attention to detail. Their team was highly professional and possessed a firm grasp on technicalities, a combination that is hard to find in the industry.”

Pam Chitwood

Product Manager, ABB

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Nick Drogo

Global Director IT, Knowles

“They helped us build a docketing app with an intuitive user interface, allowing our attorneys to track over 10,000 U.S. and international patent systems.”

Robert K Burger

COO, Sterne Kessler

Umair Bashir

CTO, Replenium

Pam Chitwood

Product Manager, ABB

Build and launch your first AI system in weeks.

Our clients

AI pilots are easy. Production AI is where most teams get stuck.

AI is being tested, but ROI is unclear

Internal teams do not have the capacity to build AI

AI pilots never reach real workflows

The scope gets too big too fast

What is an AI Pod?

AI Pod

Senior-led delivery team

AI Pod

AI agents accelerate the build

AI Pod

KPI defined before build starts

AI Pod

Fixed cost

AI Pod

Production-ready in weeks

AI Pod

Built to keep delivering

Lead AI Architect

AI Engineers

Product Designer

Specialist Streams

How an AI Pod runs

01

How an AI Pod runs

Scope and Fit:

Build & Validate

Production Launch

Measure and Hand Off

Get a free AI agent discovery sprint.

Limited slots available.

17 of 25 free sprints filled.

8 remaining.

Success Stories in Spotlight

50% faster discovery with an AI-powered knowledge sharing agent

Chris Head

GreenGro cuts support time in half with AI knowledge agent

Cut customer response times by 68% through a conversational AI agent integrated with CRM systems.

AI Support & Experience Agent

Improved forecasting accuracy by 42% using a decision-intelligence agent analyzing real-time business data.

Predictive & Decision Intelligence Agent

We’ve been recognized by the best, year after year

AMERICA’S FASTEST GROWING COMPANY

TOP 100 INSPIRING WORKPLACES 2025

FORBES COACHES COUNCIL

FINANCIAL TIMES

mogul people leader

ISO 27001 CERTIFIED

ISO 20000 CERTIFIED

ISO 9001 CERTIFIED

CMMI DEV 3 CERTIFIED

Production-ready AI in as little as 6 weeks. Let’s scope yours.

Nick Drogo

Robert K Burger

Umair Bashir

Pam Chitwood

Nick Drogo

Robert K Burger

Umair Bashir

Pam Chitwood

Latest insights & resources

USA

Saudi Arabia

Portugal

Pakistan

Strictly Necessary

Performance

Targeting

Functional

Get a free AI agent
discovery sprint.