170+

Software Engineers

50+

Successful Projects Delivery

15+

Years of Experience

10+

Industries Served

170+

Software Engineers

50+

Successful Projects Delivery

15+

Years of Experience

10+

Industries Served

170+

Software Engineers

50+

Successful Projects Delivery

15+

Years of Experience

10+

Industries Served

Move toward The Future of Decision Intelligence with Big Data

Gartner’s most recent finding strongly predicts that at least 15% of daily work decisions will be automated in the coming years due to the power of agentic AI. As for enterprises, applications are going to embody agentic AI approximately 33%.
As we have already synergized agentic AI with human expertise at Trustify Technology, our talented engineers and consultants are ready to assist your business in this movement of AI-driven decision intelligence.

Establish the right big data foundation

As data volume from multiple sources is constantly increasing, challenges keep piling up at every phase, from collecting and synthesizing to transforming and providing data related to or created by business functions. The urge to centrally integrate and manage has never been higher. Meanwhile, businesses or organizations are still longing for cost efficiency, agility, and consistency in everyday data processing operations. Our experienced data architects deeply understand the challenges these real-world scenarios present to business leaders and teams. We also believe that establishing the right big data foundation (ETL/Data Lakehouse) is the very first step in this complex data processing reality. Hence, our dedicated data architects are ready to consult, design, build, deploy, and maintain data systems with full flexibility and customization.

Interpret big data into actionable insights at enterprise scale

Once the proper data setup is in place, the next step is to use detailed and relevant data to create useful insights that can be acted upon, all while maintaining top-notch compliance and security. Additionally, agentic AI allows for a combined method that uses different AI techniques to solve complex business issues through machine learning operations (MLOps). This whole approach or process can be costly in terms of time, human, and intellectual resources for organizations or enterprises. Facing this situation with our AI & Human Synergy framework, our skilled data engineers will support your business team in using, tracking, and training complete machine learning models in their daily work. Our joint forces aim for highly defined, accurate, and governed ML models to guarantee valuable and trustworthy insights at any scale.

Enable agentic AI for automated insights and instant actions

Eventually our AI-driven solutions would result in automated insights and instant actions at every trigger event of continuous integration and development. This approach can be described as “predictive analytics”; in other words, it means responding to the crucial business question “What should we do next?” with higher confidence and lower human labor dependency. Predictive analytics have already been practical in diverse industries, especially BSFI (financial services), health tech, retail, logistics, etc. Hence, when working with our Trustify Technology team, we are always ready to bring not only our AI-driven technology solutions (i.e., NLP/image processing/prediction) but also domain expertise to enable these automated processes end-to-end.

Establish the right big data foundation

As data volume from multiple sources is constantly increasing, challenges keep piling up at every phase, from collecting and synthesizing to transforming and providing data related to or created by business functions. The urge to centrally integrate and manage has never been higher. Meanwhile, businesses or organizations are still longing for cost efficiency, agility, and consistency in everyday data processing operations. Our experienced data architects deeply understand the challenges these real-world scenarios present to business leaders and teams. We also believe that establishing the right big data foundation (ETL/Data Lakehouse) is the very first step in this complex data processing reality. Hence, our dedicated data architects are ready to consult, design, build, deploy, and maintain data systems with full flexibility and customization.

Interpret big data into actionable insights at enterprise scale

Once the proper data setup is in place, the next step is to use detailed and relevant data to create useful insights that can be acted upon, all while maintaining top-notch compliance and security. Additionally, agentic AI allows for a combined method that uses different AI techniques to solve complex business issues through machine learning operations (MLOps). This whole approach or process can be costly in terms of time, human, and intellectual resources for organizations or enterprises. Facing this situation with our AI & Human Synergy framework, our skilled data engineers will support your business team in using, tracking, and training complete machine learning models in their daily work. Our joint forces aim for highly defined, accurate, and governed ML models to guarantee valuable and trustworthy insights at any scale.

Enable agentic AI for automated insights and instant actions

Eventually our AI-driven solutions would result in automated insights and instant actions at every trigger event of continuous integration and development. This approach can be described as “predictive analytics”; in other words, it means responding to the crucial business question “What should we do next?” with higher confidence and lower human labor dependency. Predictive analytics have already been practical in diverse industries, especially BSFI (financial services), health tech, retail, logistics, etc. Hence, when working with our Trustify Technology team, we are always ready to bring not only our AI-driven technology solutions (i.e., NLP/image processing/prediction) but also domain expertise to enable these automated processes end-to-end.

Establish the right big data foundation

As data volume from multiple sources is constantly increasing, challenges keep piling up at every phase, from collecting and synthesizing to transforming and providing data related to or created by business functions. The urge to centrally integrate and manage has never been higher. Meanwhile, businesses or organizations are still longing for cost efficiency, agility, and consistency in everyday data processing operations. Our experienced data architects deeply understand the challenges these real-world scenarios present to business leaders and teams. We also believe that establishing the right big data foundation (ETL/Data Lakehouse) is the very first step in this complex data processing reality. Hence, our dedicated data architects are ready to consult, design, build, deploy, and maintain data systems with full flexibility and customization.

Interpret big data into actionable insights at enterprise scale

Once the proper data setup is in place, the next step is to use detailed and relevant data to create useful insights that can be acted upon, all while maintaining top-notch compliance and security. Additionally, agentic AI allows for a combined method that uses different AI techniques to solve complex business issues through machine learning operations (MLOps). This whole approach or process can be costly in terms of time, human, and intellectual resources for organizations or enterprises. Facing this situation with our AI & Human Synergy framework, our skilled data engineers will support your business team in using, tracking, and training complete machine learning models in their daily work. Our joint forces aim for highly defined, accurate, and governed ML models to guarantee valuable and trustworthy insights at any scale.

Enable agentic AI for automated insights and instant actions

Eventually our AI-driven solutions would result in automated insights and instant actions at every trigger event of continuous integration and development. This approach can be described as “predictive analytics”; in other words, it means responding to the crucial business question “What should we do next?” with higher confidence and lower human labor dependency. Predictive analytics have already been practical in diverse industries, especially BSFI (financial services), health tech, retail, logistics, etc. Hence, when working with our Trustify Technology team, we are always ready to bring not only our AI-driven technology solutions (i.e., NLP/image processing/prediction) but also domain expertise to enable these automated processes end-to-end.

Build AI-Driven Data Pipelines Synced with Business Processes

As your trusted AI-driven technology partner, we deeply understand the urge to address complex business workflows across sales, service, marketing, and operations with optimal costs and flexible applications. In addition to this, we also realize that common bottlenecks in big data are monolithic or scattered pipelines and systems.
Tackling these challenges, our skilled data engineers are committed to assisting your business in building and synchronizing data pipelines in a continuous loop.

Establish Data & Feature Governance for Predictive Engines

The way in which we architect and manage data infrastructure has also undergone significant changes as a result of the undeniable impact of advancements in agent-based AI. This is particularly true with regard to the consideration of efficiency, accuracy, and security at the core of any decision-making process. During this time, generative AI that is presented as intellectual assistants is lacking in granular insight quality and reliable independence to a certain extent, particularly in industries that are high-risk. When it comes to making investments in the software development life cycle (SDLC) to accomplish business objectives, we are well aware of the high stakes involved. Our AI Delivery Platform drives our role as your trusted technology partner. Our main goal is to combine the power of agentic AI with human skills to create and improve predictive systems, making sure that data management and feature control are the core of our technology.

Configure, train, and version machine learning models

While DevOps practices have become an integral part of the software development life cycle, MLOps, or machine learning operation, is emerging in parallel to resolve new day-to-day challenges or obstacles. Hence, our experienced AI engineers will assist you from the ground up by employing MLOps best practices customized to your industry or region. MLOps best practices cover all steps, including deploying, tracking, monitoring ML model drift, and versioning.

Deploy and orchestrate models for production using MLOps pipelines

MLOps methods ensure ML models remain accurate and efficient throughout their lifecycles. In a nutshell, model deployment can be smooth and seamless when ML engineers follow these essential steps:
  • Use containerization tools like Docker to package models with dependencies
  • Adopt microservices architecture to tackle each model as independent services
  • Implement version control while ensuring rollback capabilities
  • Apply cloud-based solutions (e.g, AWS SageMaker, Google AI Platform, and Azure ML)
  • When working with Trustify Technology, we are highly committed to these steps with agility and flexibility at your business growth pace.

Establish Data & Feature Governance for Predictive Engines

The way in which we architect and manage data infrastructure has also undergone significant changes as a result of the undeniable impact of advancements in agent-based AI. This is particularly true with regard to the consideration of efficiency, accuracy, and security at the core of any decision-making process. During this time, generative AI that is presented as intellectual assistants is lacking in granular insight quality and reliable independence to a certain extent, particularly in industries that are high-risk. When it comes to making investments in the software development life cycle (SDLC) to accomplish business objectives, we are well aware of the high stakes involved. Our AI Delivery Platform drives our role as your trusted technology partner. Our main goal is to combine the power of agentic AI with human skills to create and improve predictive systems, making sure that data management and feature control are the core of our technology.

Configure, train, and version machine learning models

While DevOps practices have become an integral part of the software development life cycle, MLOps, or machine learning operation, is emerging in parallel to resolve new day-to-day challenges or obstacles. Hence, our experienced AI engineers will assist you from the ground up by employing MLOps best practices customized to your industry or region. MLOps best practices cover all steps, including deploying, tracking, monitoring ML model drift, and versioning.

Deploy and orchestrate models for production using MLOps pipelines

MLOps methods ensure ML models remain accurate and efficient throughout their lifecycles. In a nutshell, model deployment can be smooth and seamless when ML engineers follow these essential steps:
  • Use containerization tools like Docker to package models with dependencies
  • Adopt microservices architecture to tackle each model as independent services
  • Implement version control while ensuring rollback capabilities
  • Apply cloud-based solutions (e.g, AWS SageMaker, Google AI Platform, and Azure ML)
  • When working with Trustify Technology, we are highly committed to these steps with agility and flexibility at your business growth pace.

Establish Data & Feature Governance for Predictive Engines

The way in which we architect and manage data infrastructure has also undergone significant changes as a result of the undeniable impact of advancements in agent-based AI. This is particularly true with regard to the consideration of efficiency, accuracy, and security at the core of any decision-making process. During this time, generative AI that is presented as intellectual assistants is lacking in granular insight quality and reliable independence to a certain extent, particularly in industries that are high-risk. When it comes to making investments in the software development life cycle (SDLC) to accomplish business objectives, we are well aware of the high stakes involved. Our AI Delivery Platform drives our role as your trusted technology partner. Our main goal is to combine the power of agentic AI with human skills to create and improve predictive systems, making sure that data management and feature control are the core of our technology.

Configure, train, and version machine learning models

While DevOps practices have become an integral part of the software development life cycle, MLOps, or machine learning operation, is emerging in parallel to resolve new day-to-day challenges or obstacles. Hence, our experienced AI engineers will assist you from the ground up by employing MLOps best practices customized to your industry or region. MLOps best practices cover all steps, including deploying, tracking, monitoring ML model drift, and versioning.

Deploy and orchestrate models for production using MLOps pipelines

MLOps methods ensure ML models remain accurate and efficient throughout their lifecycles. In a nutshell, model deployment can be smooth and seamless when ML engineers follow these essential steps:
  • Use containerization tools like Docker to package models with dependencies
  • Adopt microservices architecture to tackle each model as independent services
  • Implement version control while ensuring rollback capabilities
  • Apply cloud-based solutions (e.g, AWS SageMaker, Google AI Platform, and Azure ML)
  • When working with Trustify Technology, we are highly committed to these steps with agility and flexibility at your business growth pace.

Assist businesses at every step of the data processing path

Trustify Technology does not merely implement artificial intelligence; rather, we align it with the objectives and infrastructure of your business to unlock measurable value. We craft each stage, from conception to production, with clarity, security, and long-term impact in mind.

Discover Strategic Opportunity & Solution Blueprint

We start by aligning your business objectives with real-world AI applications. This step involves assessing operational goals, data ecosystems, user needs, and regulatory requirements:
  • For enterprises: analyze your infrastructure, data governance, and processes.
  • For product companies: identify market gaps, differentiators, and features that will help you win.
  • Define clear functional and non-functional requirements (scalability, latency, compliance).
  • Scope the project, set a realistic timeline, estimate costs, and identify potential risks.

Identify the tool: Pre-Built vs. Custom

Not every use case requires building from scratch. We help you make the right decision:
  • For enterprises: analyze your infrastructure, data governance, and processes.
  • For product companies: identify market gaps, differentiators, and features that will help you win.
  • Define clear functional and non-functional requirements (scalability, latency, compliance).
  • Scope the project, set a realistic timeline, estimate costs, and identify potential risks.

Architect the AI-Driven Solution

We architect both the AI and non-AI components to ensure a seamless experience:
  • Design scalable architecture and secure system integrations.
  • Craft intuitive UX/UI that drives adoption and aligns with end-user expectations.
  • Plan data pipelines and backend workflows tailored to your operations.

Build the Solution

Our development process combines data science, software engineering, and automation:
  • For pre-built models: fine-tune, integrate, and validate.
  • For custom models: gather, EDA, clean, train, validate, and test.
  • Software side: implement DevOps, backend logic, APIs, and QA (automated where applicable).
  • Everything is tested, secure, and aligned with high quality standards.

Deploy & Integrate Systems

We move your AI solution from development to live environments with care and precision:
  • Launch the AI/ML model in real-time conditions.
  • Address edge cases and unexpected outputs.
  • Configure cloud/on-prem infrastructure with strong security protocols.
  • Integrate the AI engine with corporate systems, third-party tools, and front-end interfaces.
  • Test for load, performance, and compatibility before going live.

Drive Adoption & Manage Changes

We ensure that your team is ready to support and scale the AI solution internally:
  • Update data management policies to improve AI readiness & reduce silos.
  • Design new workflows and role-specific guidelines for your staff.
  • Deliver clear user guides and documentation for IT teams.
  • Provide flexible training formats, including on-site, remote, or hybrid, to ensure smooth transition.

Improve & Optimize Continously

AI solutions are never “set and forget.” We provide ongoing support to evolve with your business:
  • Monitor performance and retraining models based on real-world data.
  • Enhance UX and functionality based on user feedback.
  • Address security, compatibility, or operational issues as they arise - Scale or add new AI features to match your growing needs.

Discover Strategic Opportunity & Solution Blueprint

We start by aligning your business objectives with real-world AI applications. This step involves assessing operational goals, data ecosystems, user needs, and regulatory requirements:
  • For enterprises: analyze your infrastructure, data governance, and processes.
  • For product companies: identify market gaps, differentiators, and features that will help you win.
  • Define clear functional and non-functional requirements (scalability, latency, compliance).
  • Scope the project, set a realistic timeline, estimate costs, and identify potential risks.

Identify the tool: Pre-Built vs. Custom

Not every use case requires building from scratch. We help you make the right decision:
  • For enterprises: analyze your infrastructure, data governance, and processes.
  • For product companies: identify market gaps, differentiators, and features that will help you win.
  • Define clear functional and non-functional requirements (scalability, latency, compliance).
  • Scope the project, set a realistic timeline, estimate costs, and identify potential risks.

Architect the AI-Driven Solution

We architect both the AI and non-AI components to ensure a seamless experience:
  • Design scalable architecture and secure system integrations.
  • Craft intuitive UX/UI that drives adoption and aligns with end-user expectations.
  • Plan data pipelines and backend workflows tailored to your operations.

Build the Solution

Our development process combines data science, software engineering, and automation:
  • For pre-built models: fine-tune, integrate, and validate.
  • For custom models: gather, EDA, clean, train, validate, and test.
  • Software side: implement DevOps, backend logic, APIs, and QA (automated where applicable).
  • Everything is tested, secure, and aligned with high quality standards.

Deploy & Integrate Systems

We move your AI solution from development to live environments with care and precision:
  • Launch the AI/ML model in real-time conditions.
  • Address edge cases and unexpected outputs.
  • Configure cloud/on-prem infrastructure with strong security protocols.
  • Integrate the AI engine with corporate systems, third-party tools, and front-end interfaces.
  • Test for load, performance, and compatibility before going live.

Drive Adoption & Manage Changes

We ensure that your team is ready to support and scale the AI solution internally:
  • Update data management policies to improve AI readiness & reduce silos.
  • Design new workflows and role-specific guidelines for your staff.
  • Deliver clear user guides and documentation for IT teams.
  • Provide flexible training formats, including on-site, remote, or hybrid, to ensure smooth transition.

Improve & Optimize Continously

AI solutions are never “set and forget.” We provide ongoing support to evolve with your business:
  • Monitor performance and retraining models based on real-world data.
  • Enhance UX and functionality based on user feedback.
  • Address security, compatibility, or operational issues as they arise - Scale or add new AI features to match your growing needs.

Discover Strategic Opportunity & Solution Blueprint

We start by aligning your business objectives with real-world AI applications. This step involves assessing operational goals, data ecosystems, user needs, and regulatory requirements:
  • For enterprises: analyze your infrastructure, data governance, and processes.
  • For product companies: identify market gaps, differentiators, and features that will help you win.
  • Define clear functional and non-functional requirements (scalability, latency, compliance).
  • Scope the project, set a realistic timeline, estimate costs, and identify potential risks.

Identify the tool: Pre-Built vs. Custom

Not every use case requires building from scratch. We help you make the right decision:
  • For enterprises: analyze your infrastructure, data governance, and processes.
  • For product companies: identify market gaps, differentiators, and features that will help you win.
  • Define clear functional and non-functional requirements (scalability, latency, compliance).
  • Scope the project, set a realistic timeline, estimate costs, and identify potential risks.

Architect the AI-Driven Solution

We architect both the AI and non-AI components to ensure a seamless experience:
  • Design scalable architecture and secure system integrations.
  • Craft intuitive UX/UI that drives adoption and aligns with end-user expectations.
  • Plan data pipelines and backend workflows tailored to your operations.

Build the Solution

Our development process combines data science, software engineering, and automation:
  • For pre-built models: fine-tune, integrate, and validate.
  • For custom models: gather, EDA, clean, train, validate, and test.
  • Software side: implement DevOps, backend logic, APIs, and QA (automated where applicable).
  • Everything is tested, secure, and aligned with high quality standards.

Deploy & Integrate Systems

We move your AI solution from development to live environments with care and precision:
  • Launch the AI/ML model in real-time conditions.
  • Address edge cases and unexpected outputs.
  • Configure cloud/on-prem infrastructure with strong security protocols.
  • Integrate the AI engine with corporate systems, third-party tools, and front-end interfaces.
  • Test for load, performance, and compatibility before going live.

Drive Adoption & Manage Changes

We ensure that your team is ready to support and scale the AI solution internally:
  • Update data management policies to improve AI readiness & reduce silos.
  • Design new workflows and role-specific guidelines for your staff.
  • Deliver clear user guides and documentation for IT teams.
  • Provide flexible training formats, including on-site, remote, or hybrid, to ensure smooth transition.

Improve & Optimize Continously

AI solutions are never “set and forget.” We provide ongoing support to evolve with your business:
  • Monitor performance and retraining models based on real-world data.
  • Enhance UX and functionality based on user feedback.
  • Address security, compatibility, or operational issues as they arise - Scale or add new AI features to match your growing needs.

Apply AI-driven data solutions in specific industries for best ROI

Using agentic AI and human intelligence as our main approach will help your business create, implement, and track AI-driven data solutions tailored to your specific industry. By breaking down every step along the way, we can also set up metrics for success to be analyzed after putting the data solution in place.

Fintech & Banking

Our main focus in the financial industry is to secure and optimize complex transaction platforms. We suggest and set up everything related to handling data and making predictions, including building cloud data systems, training machine learning (ML) models, and applying Natural Language Processing (NLP) to regulatory papers and transaction stories. In a nutshell, our efforts will move from retroactive analysis to prescriptive fraud prevention.

Healthcare & MedTech

Our priority in healthtech remains streamlining and automating administrative processes. Agentic AI will help process images for automatic analysis of scans like MRI and X-ray, and it will also work on understanding unstructured clinical information. Eventually this approach will provide healthcare professionals with high-quality and trustworthy insights in real time while maintaining strict HIPAA/GDPR compliance.

Logistics and the public sector

We transform global logistics by focusing on true operational resilience and route optimization. Our expertise will result in predicting potential bottlenecks, maintenance failures, and optimal staffing levels. We leverage AI advancements for automated freight inspection followed by predictive analytics of dynamic routing decisions.

Smart Home / IoT

Rather than waiting for data transmission, our architecture uses efficient ETL pipelines to preprocess petabytes of data from sensors and wearables on-device (at the Edge). Then ML models are trained to predict utility failure, optimize energy consumption, and manage device battery life. For end-users, computer vision and NLP are in place to interpret surrounding context into service queries. As a result, we provide an adaptive and intelligent home ecosystem.

Travel Tech

We will assist your business to unify disparate booking, loyalty, and behavioral data into a centralized, real-time platform. By applying AI techniques as NLP procedures, predictive engines are capable of analyzing and clustering sentiments in customer responses to nail down crucial pain points. Finally, we can bring hyper-personalized offers and maximize return on investment (ROI).

Fintech & Banking

Our main focus in the financial industry is to secure and optimize complex transaction platforms. We suggest and set up everything related to handling data and making predictions, including building cloud data systems, training machine learning (ML) models, and applying Natural Language Processing (NLP) to regulatory papers and transaction stories. In a nutshell, our efforts will move from retroactive analysis to prescriptive fraud prevention.

Healthcare & MedTech

Our priority in healthtech remains streamlining and automating administrative processes. Agentic AI will help process images for automatic analysis of scans like MRI and X-ray, and it will also work on understanding unstructured clinical information. Eventually this approach will provide healthcare professionals with high-quality and trustworthy insights in real time while maintaining strict HIPAA/GDPR compliance.

Logistics and the public sector

We transform global logistics by focusing on true operational resilience and route optimization. Our expertise will result in predicting potential bottlenecks, maintenance failures, and optimal staffing levels. We leverage AI advancements for automated freight inspection followed by predictive analytics of dynamic routing decisions.

Smart Home / IoT

Rather than waiting for data transmission, our architecture uses efficient ETL pipelines to preprocess petabytes of data from sensors and wearables on-device (at the Edge). Then ML models are trained to predict utility failure, optimize energy consumption, and manage device battery life. For end-users, computer vision and NLP are in place to interpret surrounding context into service queries. As a result, we provide an adaptive and intelligent home ecosystem.

Travel Tech

We will assist your business to unify disparate booking, loyalty, and behavioral data into a centralized, real-time platform. By applying AI techniques as NLP procedures, predictive engines are capable of analyzing and clustering sentiments in customer responses to nail down crucial pain points. Finally, we can bring hyper-personalized offers and maximize return on investment (ROI).

Fintech & Banking

Our main focus in the financial industry is to secure and optimize complex transaction platforms. We suggest and set up everything related to handling data and making predictions, including building cloud data systems, training machine learning (ML) models, and applying Natural Language Processing (NLP) to regulatory papers and transaction stories. In a nutshell, our efforts will move from retroactive analysis to prescriptive fraud prevention.

Healthcare & MedTech

Our priority in healthtech remains streamlining and automating administrative processes. Agentic AI will help process images for automatic analysis of scans like MRI and X-ray, and it will also work on understanding unstructured clinical information. Eventually this approach will provide healthcare professionals with high-quality and trustworthy insights in real time while maintaining strict HIPAA/GDPR compliance.

Logistics and the public sector

We transform global logistics by focusing on true operational resilience and route optimization. Our expertise will result in predicting potential bottlenecks, maintenance failures, and optimal staffing levels. We leverage AI advancements for automated freight inspection followed by predictive analytics of dynamic routing decisions.

Smart Home / IoT

Rather than waiting for data transmission, our architecture uses efficient ETL pipelines to preprocess petabytes of data from sensors and wearables on-device (at the Edge). Then ML models are trained to predict utility failure, optimize energy consumption, and manage device battery life. For end-users, computer vision and NLP are in place to interpret surrounding context into service queries. As a result, we provide an adaptive and intelligent home ecosystem.

Travel Tech

We will assist your business to unify disparate booking, loyalty, and behavioral data into a centralized, real-time platform. By applying AI techniques as NLP procedures, predictive engines are capable of analyzing and clustering sentiments in customer responses to nail down crucial pain points. Finally, we can bring hyper-personalized offers and maximize return on investment (ROI).

Flexible engagment models enable tailored-made offerings

We architect and modernize platforms for both startups and established enterprises, ensuring seamless integration with existing IT maturity and scaling pace.

ODC based model

For a strong inhouse IT team, this model pricing is based on headcounts to enhance holistic operational efficiency.

Project based model

For a specific initiative in a defined time range, this model pricing is based on estimated scopes of works to deliver project timely.

Managed Service model

For a total IT solution in a specific field, this model pricing is based on custom specifications to empower your interal teams move faster, safer and smarter.

Build Operate Transfer model

For a business penetrating to Vietnam market, this model pricing is based on headcounts to establish and sustain most optimal development center.

Talk to our experts

ODC based model

For a strong inhouse IT team, this model pricing is based on headcounts to enhance holistic operational efficiency.

Project based model

For a specific initiative in a defined time range, this model pricing is based on estimated scopes of works to deliver project timely.

Managed Service model

For a total IT solution in a specific field, this model pricing is based on custom specifications to empower your interal teams move faster, safer and smarter.

Build Operate Transfer model

For a business penetrating to Vietnam market, this model pricing is based on headcounts to establish and sustain most optimal development center.

ODC based model

For a strong inhouse IT team, this model pricing is based on headcounts to enhance holistic operational efficiency.

Project based model

For a specific initiative in a defined time range, this model pricing is based on estimated scopes of works to deliver project timely.

Managed Service model

For a total IT solution in a specific field, this model pricing is based on custom specifications to empower your interal teams move faster, safer and smarter.

Build Operate Transfer model

For a business penetrating to Vietnam market, this model pricing is based on headcounts to establish and sustain most optimal development center.

FAQ Method & Process

What are the benefits of applying Big Data & AI solutions with us?

The development timeline for an AI-driven data solution varies depending on the complexity of the project, the quality and quantity of available data, and the specific requirements of your business. On average, it can take anywhere from a few weeks to several months to develop and implement a robust AI solution.

The cost of developing an AI-driven big data solutions depends on factors such as project complexity, data requirements, and the scope of the solution. We provide customized quotes based on your specific needs and budget constraints.

Our teams ensure the quality and accuracy of our AI-driven data solutions through rigorous testing, validation, and continuous monitoring. Additionally, we leverage advanced techniques to train our models and regularly update them with new data to maintain high performance and reliability.

Yes, we can integrate AI solutions with your existing systems and infrastructure. Our team ensures seamless integration to enhance your current operations without disrupting your workflows.

Yes, we offer ongoing support and maintenance services to ensure your AI solutions continue to operate effectively. Our team provides regular updates, performance monitoring, and optimization to adapt to changing business needs and technological advancements.

The development timeline for an AI-driven data solution varies depending on the complexity of the project, the quality and quantity of available data, and the specific requirements of your business. On average, it can take anywhere from a few weeks to several months to develop and implement a robust AI solution.

The cost of developing an AI-driven big data solutions depends on factors such as project complexity, data requirements, and the scope of the solution. We provide customized quotes based on your specific needs and budget constraints.

Our teams ensure the quality and accuracy of our AI-driven data solutions through rigorous testing, validation, and continuous monitoring. Additionally, we leverage advanced techniques to train our models and regularly update them with new data to maintain high performance and reliability.

Yes, we can integrate AI solutions with your existing systems and infrastructure. Our team ensures seamless integration to enhance your current operations without disrupting your workflows.

Yes, we offer ongoing support and maintenance services to ensure your AI solutions continue to operate effectively. Our team provides regular updates, performance monitoring, and optimization to adapt to changing business needs and technological advancements.

The development timeline for an AI-driven data solution varies depending on the complexity of the project, the quality and quantity of available data, and the specific requirements of your business. On average, it can take anywhere from a few weeks to several months to develop and implement a robust AI solution.

The cost of developing an AI-driven big data solutions depends on factors such as project complexity, data requirements, and the scope of the solution. We provide customized quotes based on your specific needs and budget constraints.

Our teams ensure the quality and accuracy of our AI-driven data solutions through rigorous testing, validation, and continuous monitoring. Additionally, we leverage advanced techniques to train our models and regularly update them with new data to maintain high performance and reliability.

Yes, we can integrate AI solutions with your existing systems and infrastructure. Our team ensures seamless integration to enhance your current operations without disrupting your workflows.

Yes, we offer ongoing support and maintenance services to ensure your AI solutions continue to operate effectively. Our team provides regular updates, performance monitoring, and optimization to adapt to changing business needs and technological advancements.