(qtf® — 01)
OPERATIONAL AI INFRASTRUCTURE
AI automation
AI automation
AI automation
AI automation
AI automation
for teams that scale.
for teams that scale.
for scale-up teams
We design and deploy AI automation for growing companies — with deep roots in telehealth, where we automate patient intake, operations, and clinical workflows end to end.
We design and deploy custom AI systems for teams that need automation, decision
support, and operational intelligence built into their workflows.
We design and deploy custom AI systems for teams that need automation, decision support, and operational intelligence built into their workflows.
We design and deploy custom AI systems for teams that need automation,
decision support, and operational intelligence built into their workflows.
Automation over busywork
Decisions powered by data
AI built for real workflows
Production-ready intelligence
Systems that actually ship
AI integrated into operations




100+ clients
98%
client satisfaction




100+ clients
98%
client satisfaction
(qtf® — 02)
HOW WE THINK ABOUT AI
Most AI breaks when it meets real operational complexity. We design systems that stay reliable when workflows, data, and people don’t behave as expected.
Most AI breaks when it meets real operational complexity. We design systems that stay reliable when workflows, data, and people don’t behave as expected.
Most AI breaks when it meets real operational complexity. We design systems that stay reliable when workflows, data, and people don’t behave as expected.
Most AI breaks when it meets real operational complexity. We design systems that stay reliable when workflows, data, and people don’t behave as expected.
Most AI breaks when it meets real operational complexity. We design systems that stay reliable when workflows, data, and people don’t behave as expected.
We don’t start with models. We start with how decisions are made,
where processes fail, and how systems behave under pressure.
We don’t start with models. We start with how
decisions are made, where processes fail, and how
systems behave under pressure.
Konrad Sudyka
Founder & Principal Consultant
OUR CAPABILITIES
What we automate
Managed AI automation that runs your busywork, so your team doesn’t have to.
001.
AI Agents + Human-in-the-Loop
AI agents handle the repetitive steps; your team approves the decisions that matter.
002.
Document & Intake Automation
Forms, contracts, and intake packets read, extracted, and routed automatically.
003.
App Integrations
Your CRM, EHR, inbox, and billing tools connected so data moves without copy-paste.
004.
AI Assistants
Assistants trained on your SOPs that answer, draft, and triage around the clock.
Automation as a Service
Want it off your plate?
We build it, run it, monitor it, and improve it. No learning curve, no new hires, just consistent results.
Solutions by team
Operations
Hand-offs, reporting, and recurring tasks on autopilot
Sales
Lead routing, follow-ups, and CRM hygiene
Customer Support
Ticket triage and instant first responses
Finance
Invoicing, reconciliation, and approvals
HR
Onboarding, documents, and scheduling
Marketing
Lead capture, reporting, and content ops
Solutions by industry
Telehealth & Healthcare
Same-day patient scheduling instead of multi-day delays
Intake, eligibility checks, scheduling, and follow-ups automated end to end.
Professional Services
Professional Services
Client onboarding and document workflows
eCommerce
eCommerce
Order, inventory, and support automation
Real Estate
Real Estate
Lead response, leasing, and transaction paperwork
How it works
01
Audit
We map your workflows and find the highest-ROI automations.
02
Build
We design, build, and test the automations with your team in the loop.
03
Run
We operate, monitor, and optimize them as a managed service.
(qtf® — 04)
SELECTED CASES
Case studies
Case studies
Case studies
Whether you’re just exploring possibilities
or looking to scale existing tools.
Whether you’re just exploring possibilities
or looking to scale existing tools.
(qtf® — 05)
More cases

Play
What are AI Agents?
12 min overview
ACTIVITY
Operational
Decisions
+
Automated decisions
across deployed AI systems
+15%
jun.
+35%
jul.
+53%
aug.
Benchmark
System
Recovery
%
Faster operational recovery
Faster
operational recovery
after AI decision automation
No hype. Just systems
Clarity beats automation
Decisions over demos
Designed for messy reality
Systems that hold under pressure
1
2
3
4
/4
(QTF® — 06)
Process
Execution Flow
A structured process used to design, deploy, and scale AI systems across real operational environments.
001.
Audit
System Audit & Discovery
We analyze how the system actually operates across workflows, data, and decision points. This step identifies constraints and opportunities before any AI or automation is introduced.
WHAT WE ANALYZE
001.
Core operational workflows and handoffs
002.
Data sources, ownership, and consistency
003.
Manual decision points and exceptions
004.
Existing tools, integrations, and constraints
Technology Stacks
Cogni
Pulse
Synth
MindX
002.
AUTOMATION
Automation Design & Agents
We design intelligent automation systems and AI agents tailored to your operational workflows. This step translates audit insights into executable automation architecture and controlled agent behavior.
WHAT WE ANALYZE
001.
Automation-ready workflows and task clusters
002.
Decision trees, escalation paths, and guardrails
003.
System APIs and integration surface
004.
Human-in-the-loop control mechanisms
Technology Stacks
Kortx
Strat
NovaA
Cogni
003.
ARCHITECTURE
AI Strategy & Technical Architecture
We define the long-term AI direction aligned with business priorities. This step ensures that every AI initiative fits within a scalable, secure, and economically viable architecture.
WHAT WE ANALYZE
001.
Strategic objectives and ROI potential
002.
Data infrastructure maturity
003.
Build vs. buy vs. hybrid scenarios
004.
Governance, compliance, and risk models
Technology Stacks
Cogni
Nexis
Atica
GridX
004.
INFRASTRUCTURE
Data Infrastructure & Foundations
We build the structured data layer required for reliable AI systems. This step transforms fragmented data into consistent, model-ready infrastructure.
WHAT WE ANALYZE
001.
Data sources and ingestion pipelines
002.
Data quality, gaps, and normalization
003.
Storage architecture and retrieval performance
004.
Security, privacy, and access control
Technology Stacks
Logix
Axiom
Lumen
Pulse
(QTF® — 06)
Process
Execution Flow
A structured process used to design, deploy, and scale AI systems across real operational environments.
001.
Audit
System Audit & Discovery
We analyze how the system actually operates across workflows, data, and decision points. This step identifies constraints and opportunities before any AI or automation is introduced.
WHAT WE ANALYZE
001.
Core operational workflows and handoffs
002.
Data sources, ownership, and consistency
003.
Manual decision points and exceptions
004.
Existing tools, integrations, and constraints
Technology Stacks
Cogni
Pulse
Synth
MindX

1
2
3
4
/4
002.
AUTOMATION
Automation Design & Agents
We design intelligent automation systems and AI agents tailored to your operational workflows. This step translates audit insights into executable automation architecture and controlled agent behavior.
WHAT WE ANALYZE
001.
Automation-ready workflows and task clusters
002.
Decision trees, escalation paths, guardrails
003.
System APIs and integration surface
004.
Human-in-the-loop control mechanisms
Technology Stacks
Kortx
Strat
NovaA
Cogni

1
2
3
4
/4
003.
ARCHITECTURE
AI Strategy & Technical Architecture
We define the long-term AI direction aligned with business priorities. This step ensures that every AI initiative fits within a scalable, secure, and economically viable architecture.
WHAT WE ANALYZE
001.
Strategic objectives and ROI potential
002.
Data infrastructure maturity
003.
Build vs. buy vs. hybrid scenarios
004.
Governance, compliance, and risk models
Technology Stacks
Cogni
Nexis
Atica
GridX

1
2
3
4
/4
004.
INFRASTRUCTURE
Data Infrastructure & Foundations
We build the structured data layer required for reliable AI systems. This step transforms fragmented data into consistent, model-ready infrastructure.
WHAT WE ANALYZE
001.
Data sources and ingestion pipelines
002.
Data quality, gaps, and normalization
003.
Storage architecture and retrieval performance
004.
Security, privacy, and access control
Technology Stacks
Logix
Axiom
Lumen
Pulse

1
2
3
4
/4
(QTF® — 06)
Process
Execution Flow
A structured process used to design, deploy, and scale AI systems across operational environments.
001.
Audit
System Audit & Discovery
We analyze workflows, data, and decision points to identify constraints and opportunities before implementation begins.
001.
Core operational workflows and handoffs
002.
Data sources, ownership, and consistency
003.
Manual decision points and exceptions
004.
Tools, integrations, and constraints
Technology Stacks

1
2
3
4
/4
002.
AUTOMATION
Automation Design & Agents
We design AI agents and automation systems tailored to your workflows, turning audit insights into practical automation architecture.
001.
Automation-ready workflows and task clusters
002.
Decision trees, and guardrails
003.
System APIs and integration surface
004.
Human-in-the-loop control mechanisms
Technology Stacks

1
2
3
4
/4
003.
ARCHITECTURE
AI Strategy & Technical Architecture
We define a long-term AI strategy aligned with business goals, ensuring every initiative supports scalable and sustainable growth.
001.
Strategic objectives and ROI potential
002.
Data infrastructure maturity
003.
Build vs. buy vs. hybrid scenarios
004.
Governance, compliance, and risk models
Technology Stacks

1
2
3
4
/4
004.
INFRASTRUCTURE
Data Infrastructure & Foundations
We build the structured data layer required for reliable AI systems. We transform fragmented data into consistent, model-ready infrastructure.
001.
Data sources and ingestion pipelines
002.
Data quality, gaps, and normalization
003.
Storage architecture and performance
004.
Security, privacy, and access control
Technology Stacks

1
2
3
4
/4
1
2
3
4
/4
(QTF® — 06)
Process
Execution Flow
A structured process used to design, deploy, and scale AI systems across real operational environments.
001.
Audit
System Audit & Discovery
We analyze workflows, data, and decision points to identify constraints and opportunities before implementation begins.
WHAT WE ANALYZE
001.
Core operational workflows and handoffs
002.
Data sources, ownership, and consistency
003.
Manual decision points and exceptions
004.
Existing tools, integrations, and constraints
Technology Stacks
Cogni
Pulse
Synth
MindX
002.
AUTOMATION
Automation Design & Agents
We design AI agents and automation systems tailored to your workflows, turning audit insights into practical automation architecture.
WHAT WE ANALYZE
001.
Automation-ready workflows and task clusters
002.
Decision trees, escalation paths, and guardrails
003.
System APIs and integration surface
004.
Human-in-the-loop control mechanisms
Technology Stacks
Kortx
Strat
NovaA
Cogni
003.
ARCHITECTURE
AI Strategy & Technical Architecture
We define a long-term AI strategy aligned with business goals, ensuring every initiative supports scalable and sustainable growth.
WHAT WE ANALYZE
001.
Strategic objectives and ROI potential
002.
Data infrastructure maturity
003.
Build vs. buy vs. hybrid scenarios
004.
Governance, compliance, and risk models
Technology Stacks
Cogni
Nexis
Atica
GridX
004.
INFRASTRUCTURE
Data Infrastructure & Foundations
We build the structured data layer required for reliable AI systems. This step transforms fragmented data into consistent, model-ready infrastructure.
WHAT WE ANALYZE
001.
Data sources and ingestion pipelines
002.
Data quality, gaps, and normalization
003.
Storage architecture and retrieval performance
004.
Security, privacy, and access control
Technology Stacks
Logix
Axiom
Lumen
Pulse
1
2
3
4
/4
(QTF® — 06)
Process
Execution Flow
A structured process used to design, deploy, and scale AI systems across real operational environments.
001.
Audit
System Audit & Discovery
We analyze workflows, data, and decision points to identify constraints and opportunities before implementation begins.
WHAT WE ANALYZE
001.
Core operational workflows and handoffs
002.
Data sources, ownership, and consistency
003.
Manual decision points and exceptions
004.
Existing tools, integrations, and constraints
Technology Stacks
Cogni
Pulse
Synth
MindX
002.
AUTOMATION
Automation Design & Agents
We design AI agents and automation systems tailored to your workflows, turning audit insights into practical automation architecture.
WHAT WE ANALYZE
001.
Automation-ready workflows and task clusters
002.
Decision trees, escalation paths, and guardrails
003.
System APIs and integration surface
004.
Human-in-the-loop control mechanisms
Technology Stacks
Kortx
Strat
NovaA
Cogni
003.
ARCHITECTURE
AI Strategy & Technical Architecture
We define a long-term AI strategy aligned with business goals, ensuring every initiative supports scalable and sustainable growth.
WHAT WE ANALYZE
001.
Strategic objectives and ROI potential
002.
Data infrastructure maturity
003.
Build vs. buy vs. hybrid scenarios
004.
Governance, compliance, and risk models
Technology Stacks
Cogni
Nexis
Atica
GridX
004.
INFRASTRUCTURE
Data Infrastructure & Foundations
We build the structured data layer required for reliable AI systems. This step transforms fragmented data into consistent infrastructure.
WHAT WE ANALYZE
001.
Data sources and ingestion pipelines
002.
Data quality, gaps, and normalization
003.
Storage architecture and retrieval performance
004.
Security, privacy, and access control
Technology Stacks
Logix
Axiom
Lumen
Pulse
What We Deliver
(®)
(qtf® — 07)
SYSTEM OUTPUT
We design and build AI systems that operate
inside real workflows — from idea to production.
© ‒ 001.
Operational AI Expertise
We specialize in AI systems designed for real operational environments — not experiments or isolated prototypes.
© ‒ 001.
Operational AI Expertise
We specialize in AI systems designed for real operational environments — not experiments or isolated prototypes.
© ‒ 001.
Operational AI Expertise
We build reliable AI systems for real-world operations.
© ‒ 001.
Operational AI Expertise
We build reliable AI systems for real-world operations.
Konrad Sudyka©
© ‒ 002.
Systems That Actually Ship
Our work focuses on production-ready AI tools that integrate with existing infrastructure and workflows.
© ‒ 002.
Systems That Actually Ship
Our work focuses on production-ready AI tools that integrate with existing infrastructure and workflows.
© ‒ 002.
Systems That Actually Ship
Production-ready AI tools built for existing systems and workflows.
© ‒ 002.
Systems That Actually Ship
Production-ready AI tools built for existing systems and workflows.
© ‒ 003.
Deep Technical Ownership
From architecture to deployment, our team builds and operates the systems we design.
© ‒ 003.
Deep Technical Ownership
From architecture to deployment, our team builds and operates the systems we design.
© ‒ 003.
Deep Technical Ownership
We build and operate every system we design.
© ‒ 004.
Real Business Impact
Every system is built to improve measurable outcomes — operational speed, reliability, and decision quality.
© ‒ 004.
Real Business Impact
Every system is built to improve measurable outcomes — operational speed, reliability, and decision quality.
© ‒ 005.
Clear Collaboration
Transparent communication, defined milestones, and full visibility across every stage of the project.
© ‒ 005.
Clear Collaboration
Transparent communication, defined milestones, and full visibility across every stage of the project.
© ‒ 005.
Clear Collaboration
Transparent communication and full visibility at every stage.
© ‒ 005.
Clear Collaboration
Transparent communication and full visibility at every stage.
(qtf® — 08)
OUR JOURNEY
Engineering systems that turn
complex work into automation
Engineering systems
that turn complex work into automation
From early automation tools to building
production AI systems used by growing companies.
2019 — 2020
Marketing Roots
Started in performance marketing and growth for startups across industries.
2020 — 2022
Founding ElevatedHealth
Built a telehealth platform from scratch — and automated its operations end to end.
2022 — 2024
Consulting & AI Projects
Helped 100+ clients with growth strategy, financial modeling, and AI implementation.
2024 — Present
AI Automation Consultancy
Today we build AI automation for growing companies.
2019 — 2020
Marketing Roots
We started as a small engineering team focused on automation and internal tools.
2020 — 2022
Founding ElevatedHealth
Built a telehealth platform from scratch — and automated its operations end to end.
2022 — 2024
Consulting & AI Projects
Helped 100+ clients with growth strategy, financial modeling, and AI implementation.
2024 — Present
AI Automation Consultancy
Today we design production AI systems used across multiple industries.
2019 — 2020
Small Team Beginnings
We started as a small engineering team focused on automation and internal tools.
2020 — 2022
First AI Projects
Built a telehealth platform from scratch — and automated its operations end to end.
2022 — 2024
Systems Expansion
Helped 100+ clients with growth strategy, financial modeling, and AI implementation.
2024 — Present
Operational AI Studio
Today we design production AI systems used across multiple industries.
2019 — 2020
Marketing Roots
We started as a small team focused on automation and internal tools.
2020 — 2022
Founding ElevatedHealth
Built a telehealth platform from scratch — and automated its operations end to end.
2022 — 2024
Consulting & AI Projects
Our work expanded into full AI systems and operational infrastructure.
2024 — Present
AI Automation Consultancy
Today we design production AI systems used across multiple industries.
2019 — 2020
Marketing Roots
We started as a small team focused on automation and internal tools.
2020 — 2022
Founding ElevatedHealth
Built a telehealth platform from scratch — and automated its operations end to end.
2022 — 2024
Consulting & AI Projects
Our work expanded into full AI systems and operational infrastructure.
2024 — Present
AI Automation Consultancy
Today we design production AI systems used across multiple industries.
(qtf® — 10)
ENGAGEMENT MODELS
Access plans
Access plans
Access plans
Flexible engagement models for teams
exploring or scaling AI systems.
Campaign setup used to take our team most of a week. Now creators are matched, briefed, and live before our old process would have cleared legal.

Maya Lindqvist
Head of Growth, Swipeminds Ltd
We had automated pieces of this before and it never stuck. This time the system matched how our teams actually hand work to each other, so people stopped working around it.

Maya Lindqvist
Head of Growth, Swipeminds Ltd
© ‒ 001.
AI Automation Setup
A one-time engagement — we design and deploy AI automation for your highest-impact workflows, done for you.
from
$
Timeframe:
Per project — typically delivered in 2-3 weeks
What’s included:
Workflow audit and automation plan
Build-out of one core automation system
Integrations with your existing tools
Team training and handoff
30 days of post-launch support
© ‒ 001.
AI Automation Setup
We analyze your systems, workflows, and data landscape to identify high-impact AI opportunities and define the technical direction.
from
$
Timeframe:
Per project — typically delivered in 2-3 weeks
What’s included:
Workflow audit and automation plan
Build-out of one core automation system
Integrations with your existing tools
Team training and handoff
30 days of post-launch support
© ‒ 001.
AI Automation Setup
We analyze your systems, workflows, and data to identify high-impact AI opportunities.
from
$
Timeframe:
2–3 weeks
What’s included:
Process Workflow Analysis
AI Opportunity Identification
Data Structure Review
System Architecture Definition
Pipeline Infrastructure Design
© ‒ 001.
AI Automation Setup
We analyze your systems, workflows, and data landscape to identify high-impact AI opportunities.
from
$
Timeframe:
Per project — typically delivered in 2-3 weeks
What’s included:
Analysis of existing processes and manual operations
Build-out of one core automation system
Integrations with your existing tools
Team training and handoff
30 days of post-launch support
© ‒ 001.
AI Automation Setup
We analyze your systems, workflows, and data landscape to identify high-impact AI opportunities
from
$
Timeframe:
Per project — typically delivered in 2-3 weeks
What’s included:
Analysis of existing processes
Identification of high-impact AI
Review of data structure
Definition of AI system architecture
Design of data pipelines
© ‒ 002.
AI Consulting & Build-Out
Full AI consulting plus build-out of every system your operation needs — from strategy through deployed automation.
from
$
Timeframe:
Per project — typically delivered in 4-8 weeks
What’s included:
End-to-end workflow and systems audit
AI strategy and system architecture
Build-out of all core automations
EHR, CRM, and tool integrations
Team training, docs, and support
© ‒ 002.
AI Consulting & Build-Out
Designing the architecture, data pipelines, and technical foundation required to deploy AI systems in production.
from
$
Timeframe:
Per project — typically delivered in 4-8 weeks
What’s included:
End-to-end workflow and systems audit
AI strategy and system architecture
Build-out of all core automations
EHR, CRM, and tool integrations
Team training, docs, and support
© ‒ 002.
AI Consulting & Build-Out
Designing the architecture and technical foundation required to deploy AI systems.
from
$
Timeframe:
3–5 weeks
What’s included:
Process Workflow Analysis
AI Opportunity Identification
Data Structure Review
System Architecture Definition
Pipeline Infrastructure Design
© ‒ 002.
AI Consulting & Build-Out
Designing the architecture, data pipelines, and technical foundation required to deploy AI systems in production.
from
$
Timeframe:
Per project — typically delivered in 4-8 weeks
What’s included:
Analysis of existing processes and manual operations across
AI strategy and system architecture
Build-out of all core automations
EHR, CRM, and tool integrations
Team training, docs, and support
© ‒ 002.
AI Consulting & Build-Out
Designing the architecture and data pipelines required to deploy AI systems
from
$
Timeframe:
Per project — typically delivered in 4-8 weeks
What’s included:
Analysis of existing processes
Identification of high-impact AI
Review of data structure
Definition of AI system architecture
Design of data pipelines
© ‒ 003.
Flagship Transformation
Our highest-touch engagement — a complete operational transformation with Konrad embedded as your AI lead.
from
$
Timeframe:
Per project — typically delivered in 8-12+ weeks
What’s included:
Everything in AI Consulting & Build-Out
Custom AI systems and dashboards
Weekly strategy sessions with Konrad
90 days of post-launch optimization
© ‒ 003.
Flagship Transformation
Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.
from
$
Timeframe:
Per project — typically delivered in 8-12+ weeks
What’s included:
Everything in AI Consulting & Build-Out
Custom AI systems and dashboards
Weekly strategy sessions with Konrad
90 days of post-launch optimization
© ‒ 003.
Flagship Transformation
Building, integrating, and deploying AI systems directly into your existing tools and workflows.
from
$
Timeframe:
4–8 weeks
What’s included:
Process Workflow Analysis
AI Opportunity Identification
System Architecture Definition
Pipeline Infrastructure Design
© ‒ 003.
Flagship Transformation
Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.
from
$
Timeframe:
Per project — typically delivered in 8-12+ weeks
What’s included:
Analysis of existing processes and manual operations
Custom AI systems and dashboards
Weekly strategy sessions with Konrad
90 days of post-launch optimization
© ‒ 003.
Flagship Transformation
Building, integrating, and deploying AI systems directly into your existing tools.
from
$
Timeframe:
Per project — typically delivered in 8-12+ weeks
What’s included:
Analysis of existing processes
Identification of high-impact AI
Definition of AI system architecture
Design of data pipelines
® - 004.
Consulting Retainer
Ongoing strategic consulting — growth, automation, and operations guidance on call every month.
from
$
Timeframe:
Per month — cancel anytime
What’s included:
Weekly or bi-weekly strategy calls
Priority async access to Konrad
Ongoing automation improvements
Metrics review and optimization
Vendor, tooling, and hiring guidance
® - 004.
Consulting Retainer
Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.
from
$
Timeframe:
Per month — cancel anytime
What’s included:
Weekly or bi-weekly strategy calls
Priority async access to Konrad
Ongoing automation improvements
Metrics review and optimization
Vendor, tooling, and hiring guidance
® - 004.
Consulting Retainer
Building, integrating, and deploying AI systems directly into your existing tools and workflows.
from
$
Timeframe:
4–8 weeks
What’s included:
Process Workflow Analysis
AI Opportunity Identification
Data Structure Review
System Architecture Definition
Pipeline Infrastructure Design
® - 004.
Consulting Retainer
Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.
from
$
Timeframe:
Per month — cancel anytime
What’s included:
Analysis of existing processes and manual operations
Priority async access to Konrad
Ongoing automation improvements
Metrics review and optimization
Vendor, tooling, and hiring guidance
® - 004.
Consulting Retainer
Building, integrating, and deploying AI systems directly into your existing tools.
from
$
Timeframe:
Per month — cancel anytime
What’s included:
Analysis of existing processes
Identification of high-impact AI
Review of data structure
Definition of AI system architecture
Design of data pipelines
® - 005.
Google Ads Management
Done-for-you Google PPC — campaigns built, optimized, and scaled for profitable customer acquisition.
from
$
Timeframe:
Per month — 3-month minimum
What’s included:
Campaign strategy and build-out
Ad copy and creative testing
Conversion tracking setup
Weekly bid and budget optimization
Monthly performance reporting
® - 005.
Google Ads Management
Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.
from
$
Timeframe:
Per month — 3-month minimum
What’s included:
Campaign strategy and build-out
Ad copy and creative testing
Conversion tracking setup
Weekly bid and budget optimization
Monthly performance reporting
® - 005.
Google Ads Management
Building, integrating, and deploying AI systems directly into your existing tools and workflows.
from
$
Timeframe:
4–8 weeks
What’s included:
Process Workflow Analysis
AI Opportunity Identification
Data Structure Review
System Architecture Definition
Pipeline Infrastructure Design
® - 005.
Google Ads Management
Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.
from
$
Timeframe:
Per month — 3-month minimum
What’s included:
Analysis of existing processes and manual operations
Ad copy and creative testing
Conversion tracking setup
Weekly bid and budget optimization
Monthly performance reporting
® - 005.
Google Ads Management
Building, integrating, and deploying AI systems directly into your existing tools.
from
$
Timeframe:
Per month — 3-month minimum
What’s included:
Analysis of existing processes
Identification of high-impact AI
Review of data structure
Definition of AI system architecture
Design of data pipelines

(qtf® — 13)
frequently asked questions
Questions
that matters
Core Questions
A clear set of answers about how we design, build,
and deploy AI systems in real environments.
A clear set of answers about how we design, build, and deploy AI systems.
001.
Is this just a wrapper for ChatGPT?
Absolutely not. While we leverage powerful models like GPT-4o or Claude, the real value lies in our custom architecture. We build specialized RAG (Retrieval-Augmented Generation) systems that sync with your private data silos, ensuring the AI operates within your business context, not just general knowledge.
001.
Is this just a wrapper for ChatGPT?
Absolutely not. While we leverage powerful models like GPT-4o or Claude, the real value lies in our custom architecture. We build specialized RAG (Retrieval-Augmented Generation) systems that sync with your private data silos, ensuring the AI operates within your business context, not just general knowledge.
002.
How long does it take to see a return on investment (ROI)?
Most companies begin to see measurable impact within the first few months. By automating repetitive workflows or improving decision speed, AI systems often reduce operational costs and unlock new capacity across teams.
002.
How long does it take to see a return on investment (ROI)?
Most companies begin to see measurable impact within the first few months. By automating repetitive workflows or improving decision speed, AI systems often reduce operational costs and unlock new capacity across teams.
002.
How long does it take to see ROI?
Most companies begin to see measurable impact within the first few months. By automating repetitive workflows or improving decision speed, AI systems often reduce operational costs and unlock new capacity across teams.
003.
Can we integrate these AI agents with our existing software stack?
Yes. Our systems are designed to integrate with existing tools through APIs, databases, and internal services. We adapt the architecture to your stack so AI works within your current workflows, not outside them.
003.
Can we integrate these AI agents with our existing software stack?
Yes. Our systems are designed to integrate with existing tools through APIs, databases, and internal services. We adapt the architecture to your stack so AI works within your current workflows, not outside them.
003.
Can we integrate AI agents with our existing software stack?
Yes. Our systems are designed to integrate with existing tools through APIs, databases, and internal services. We adapt the architecture to your stack so AI works within your current workflows, not outside them.
003.
Can we integrate AI agents with our existing stack?
Yes. Our systems are designed to integrate with existing tools through APIs, databases, and internal services. We adapt the architecture to your stack so AI works within your current workflows, not outside them.
004.
How do you ensure our sensitive data stays secure?
Security is built into the architecture from the start. We use controlled access layers, encrypted storage, and isolated processing environments to ensure your data remains protected and fully under your control.
004.
How do you ensure our sensitive data stays secure?
Security is built into the architecture from the start. We use controlled access layers, encrypted storage, and isolated processing environments to ensure your data remains protected and fully under your control.
005.
Will AI hallucinations affect the quality of our output?
We reduce hallucinations through system design, not just model choice. Retrieval systems, validation layers, and controlled prompts ensure outputs are grounded in your real data and business context.
005.
Will AI hallucinations affect the quality of our output?
We reduce hallucinations through system design, not just model choice. Retrieval systems, validation layers, and controlled prompts ensure outputs are grounded in your real data and business context.
(qtf® — 14)
OUR CONTACT
Let's talk
Let's talk
Let's talk
Bring your system, your workflow, or your idea.
We’ll help you understand what it takes to build and deploy it.
Bring your system, your workflow, or your idea.
We’ll help you understand what it takes to build.
hello@konradsudyka.com
No hype. Just systems
No hype. Just systems
No hype. Just systems
Clarity beats automation
Clarity beats automation
Clarity beats automation
Decisions over demos
Decisions over demos
Decisions over demos
Designed for messy reality
Designed for messy reality
Designed for messy reality
Systems that hold under pressure
Systems that hold under pressure
Systems that hold under pressure






