AI Workflow Automation Platform
PractIQ is an intelligent platform that standardizes and automates daily work using AI tools, delivering repeatable results and measurable business impact.
Smart automation, repeatable outcomes
PractIQ standardizes and automates key IT practices across the entire SDLC, allowing you to create your own solutions or leverage ready-made ones based on the best industry standards. With AI agents embedded into operations, IT teams can implement changes faster, reduce errors, and improve efficiency — all without costly process or tool overhauls.
Work automation
Standardize and automate the entire cycle — from analysis to testing — with ready-made practices and AI agents that support teams in their daily work.
Smart workflow
By leveraging ML models and collaborative AI agents, the platform automates repetitive practices and operational outcomes, increasing organizational scalability and efficiency.
AI agentic teams
AI agents embedded in the platform support humans in decision-making, take on part of the responsibility, and automate outcomes — not just tasks.
Intelligent automation technology
Our solution is designed around two models. You can either use ready-made, proven IT practices — or automate your own processes, tailored to the way your organization operates.
Use ready-made practices
Access a repository of core practices aligned with specific technologies and frameworks. Select and adapt them to fit your organization.
Automate your own practices
Automate your IT practices using a 5-step model that eliminates manual configuration and ensures effectiveness.
AI empowering every stage of your SDLC
Automate your IT practices based on a 5-step model that eliminates manual configuration and ensures effectiveness.
ANALYSIS: better decisions from the start
Business and technical requirements analysis supported by AI agents. Accelerate project decisions and reduce the risk of incorrect assumptions.
ARCHITECTURE: consistent project foundations
Architecture design based on standards and best practices. Build solid foundations that simplify further development and system integration.
DESIGN: faster, more accurate solutions
Modeling and documentation supported by ready-made templates and automation. Achieve project consistency and shorter preparation times.
DEVELOPMENT: AI-assisted coding
Implementation supported by intelligent agents and ready-to-use components. Boost team productivity and code quality with less effort.
QA: higher quality from the start
Automation of testing and quality verification at every stage of the SDLC. Detect errors faster, reduce costs, and deliver better products.
ANALYSIS: better decisions from the start
Business and technical requirements analysis supported by AI agents. Accelerate project decisions and reduce the risk of incorrect assumptions.
ARCHITECTURE: consistent project foundations
Architecture design based on standards and best practices. Build solid foundations that simplify further development and system integration.
DESIGN: faster, more accurate solutions
Modeling and documentation supported by ready-made templates and automation. Achieve project consistency and shorter preparation times.
DEVELOPMENT: AI-assisted coding
Implementation supported by intelligent agents and ready-to-use components. Boost team productivity and code quality with less effort.
QA: higher quality from the start
Automation of testing and quality verification at every stage of the SDLC. Detect errors faster, reduce costs, and deliver better products.
Automate your own practices
With PractIQ, you can design and automate your own work practices — fully tailored to your organization’s needs. The platform allows you to combine industry standards, AI agents, and ready-made ML models into flexible solutions that support teams in their daily tasks and accelerate goal achievement.
What are practices?
A practice is a repeatable and structured way of achieving a specific goal within an organization. It defines what needs to be done, in what order, by whom, and what outputs are produced as a result. Each practice is carried out according to established standards to achieve a defined business or technological objective.
Work product
Artifacts, end productscreated as part of a practice(e.g. documents, models,code).
Competency
AI agents needed toperform actions.
Alpha
An entity that we manage aspart of a practice
(e.g. requirements,architecture).
Alpha State
The states of development ofthis entity, defining theprogress of work.
Standards
Your organization’sstandards that we workby.
Activity
Actions and steps thatimplement the practice.
Checklist
Every alpha state has its own checklist.
How to create your own practices?
PractIQ allows you to build practices from scratch or adapt existing standards to your organization’s needs. Every step — from identification and design to defining AI agents, testing, and optimization — is supported by tools that ensure consistency, flexibility, and tangible business benefits.
Practice identification
Select a practice from the IT4IT model or design a new one. Ready-made solutions can be adapted to fit your organization’s specific context.
Creating AI roles
Define AI agents that will support the practice. Each agent receives clear rules and instructions to effectively assist the team in performing tasks.
Building the workflow
Design the flow and expected outcomes of the practice, following industry best standards and integrating with your existing tools.
Testing and improvement
Validate the practice in real-world conditions. Iteratively refine it and eliminate edge cases to ensure reliability across different scenarios.
Cost optimization
Ensure the practice runs efficiently and cost-effectively — using smaller AI models where large computational resources aren’t required.
Practice identification
Select a practice from the IT4IT model or design a new one. Ready-made solutions can be adapted to fit your organization’s specific context.
Creating AI roles
Define AI agents that will support the practice. Each agent receives clear rules and instructions to effectively assist the team in performing tasks.
Building the workflow
Design the flow and expected outcomes of the practice, following industry best standards and integrating with your existing tools.
Testing and improvement
Validate the practice in real-world conditions. Iteratively refine it and eliminate edge cases to ensure reliability across different scenarios.
Cost optimization
Ensure the practice runs efficiently and cost-effectively — using smaller AI models where large computational resources aren’t required.
Modular architecture
PractIQ’s architecture is designed in a modular way to ensure flexibility and scalability. Each system component serves a specific purpose — from embedding AI into operational practices and managing agents to integrating with existing IT environments. Together, they form a cohesive ecosystem that automates work outcomes and enables seamless collaboration between humans and AI.
Human in the loop
The purpose of this module is to ensure continuous human oversight and the ability to intervene at selected stages of practice execution.
Conversational interfaces (Chat), available via a web browser and embedded within domain applications (in development), enabling natural interaction with the system.
Integration with IDEs, particularly Visual Studio Code, providing contextual support during programming, refactoring, testing, and code review.
The ability to accept, modify, or revert automated actions proposed by the system in supervised mode.
Knowladge Layer
This module is responsible for collecting, organizing, and utilizing domain and technical knowledge in the context of the organization’s practices
A knowledge base containing definitions of practices, rules, and expertise.
The ability to train or adapt LLM responses to the specific realities of the organization.
Support for leveraging existing practices used within the organization or adopting those proposed by Inteca.
Data Context Layer
This module provides the full organizational context necessary for intelligent task automation.
It enables access to data records and the construction of a knowledge graph that supports decision-making by both the Agent and the human.
JIRA integration— reading and modifying backlog items, tasks, and bugs
Enterprise Architect integration — access to architecture diagrams and domain models
Wiki, Confluence, Notion integration — documentation context
Model Execution Layer
This layer is responsible for performing tasks powered by generative artificial intelligence.
Support for multiple LLM models (e.g., OpenAI GPT, Claude, LLaMA, local models).
Dynamic selection of the model based on the task (e.g., coding, document analysis, test creation). It enables the creation of a virtual AI team supported by specialized knowledge and practices relevant to its field of activity.
The ability to extend the platform with fine-tuned models trained on organizational data.
Orchestration Layer
A central component that supports integration of the remaining modules and orchestrates data and tasks. Its functions include:
Configuration and construction of tools / Tool Servers (MCPServers)
Integration with language models
Conversation memory management
Data/Knowledge Ingestion — extracting data/knowledge from domain systems
A2A (in development) — integration using the Agent-to-Agent protocol (i.e., collaboration between agents originating from different platforms, tools, or organizations)
Distributing tasks across modules and controlling data flow
Monitoring and logging
Cloud-Native /
On-Premise
Flexible deployment in under 30 days.
PractIQ runs seamlessly in both cloud-native and on-premise environments. With an API-first approach, it easily integrates with DevOps tools and knowledge bases. It ensures the highest level of security (Security by Design) and provides a scalable AI infrastructure — ready to support multiple teams and practices.
We deliver comprehensive training and change management, enabling fast and complete adoption across the organization.
The system is supported by a dedicated technical team and regular performance reviews.
Contact Us
We’re here to answer your questions.
Ready to shift from automating actions to automating outcomes?
Discover how PractIQ transforms the way your organization works.
The technology behind smarter automation
PractIQ is an AI workflow automation platform that bridges people, processes, and machine intelligence.
Built on a modular architecture, it enables organizations to design, adapt, and automate workflows across business and IT — ensuring repeatability, scalability, and measurable outcomes.
Unlike traditional RPA or task-based automation tools, PractIQ operates at the practice level — automating how teams collaborate, make decisions, and deliver results.
It transforms proven methods into living, intelligent workflows supported by AI agents and machine learning models.
Modular architecture for flexible scaling
PractIQ’s modular architecture connects all key components of AI-powered automation — from workflow engines to AI orchestration.
Each module is designed to be adaptive, interoperable, and scalable across cloud and on-premise environments.
This allows organizations to extend automation capabilities step-by-step — without rebuilding their existing technology stack.
Key components include:
- AI Agents Framework – defines roles, rules, and behaviors for specialized AI agents.
- ML Model Layer – integrates and trains machine learning models to enhance automation accuracy.
- Workflow Engine – orchestrates business and IT processes end-to-end, ensuring consistency and context.
- Integration Layer – connects PractIQ with enterprise tools and systems (ERP, CRM, DevOps pipelines, etc.).
Agentic AI teams – collaboration redefined
At the heart of PractIQ’s technology are agentic AI teams — dynamic groups of AI agents collaborating with people to execute and optimize workflows.
Each agent is context-aware, goal-oriented, and capable of learning from experience.
Together, they enable continuous improvement and repeatable performance at scale — a foundation for intelligent operations.
AI and ML integration for real-world context
PractIQ integrates AI and ML models directly into workflows — embedding intelligence where it matters most: inside real business and IT practices.
From analyzing code quality in the SDLC to optimizing financial operations or compliance reporting, AI agents use contextual data to deliver consistent, high-quality outcomes.
SDLC standardization and automation
For software development teams, PractIQ provides an intelligent automation layer across the entire SDLC — from design to deployment.
By standardizing workflows and automating repetitive practices, it accelerates delivery, ensures compliance, and improves collaboration between development and operations teams.
PractIQ doesn’t replace developers — it enhances their capabilities, turning best practices into automated, adaptive workflows.
Why PractIQ technology?
- Modular and scalable – grow automation at your own pace.
- Intelligent and adaptive – powered by ML and contextual data.
- Human-centric – designed for collaboration between people and AI.
- Outcome-driven – focused on measurable, repeatable results.
