TEKStack AI - Technology stack supported by AI

Data-Driven application development platform, specialized in building cloud-native applications. Supported by open source and production-ready.

TEKStack AI draws its strength from how it accommodates an end-to-end application development lifecycle, with a focus on DevOps, data engineering, data ingestion and pre-processing, smart data lake design, and lightweight machine learning (ML) pipelines.

Replatforming
Modern Applications
Kubernetes DevOps
Enterprise Search
Smart Data Lake
End-to-End Machine Learning
TEKStack AI
Applications and Insights

Create modern applications using state-of-the-art technology

Technology can make everyone’s job easier – when you take a holistic and human-centric approach.

TEKStack AI is built from the ground-up to support your data-driven applications. Save time and money by using a cloud-native platform for your next project. TEKStack AI can be used for your new project or expand your current offerings. Use the platform to support your full data journey, from inception to insights, to successful customer engagements.

Cloud-Native
Data-Driven
Scalable and Secure
Modern Infrastructure
Microservices

Delivering amazing Kubernetes applications

Expand your limits and enhance your productivity – so you can be more agile with evolving customer needs and market shifts.

TEKStack AI is built on the foundation of Kubernetes to make your business in the cloud faster, more secure, and scalable. TEKStack AI saves you money by delivering your application to the end user faster. Our DevOps features support your enterprise applications by monitoring and reacting to your applications needs in real time. With TEKStack AI, continuous integration and continuous delivery, we can integrate and automate pipelines.

100% GitOps Based
Configuration as Code
Declarative Pipelines
Observability
Cloud Agnostic (AWS | GCP | Azure)
High Dev-Prod Parity
DevOps - Kubernetes
Machine Learning

Data experts alongside a comprehensive end-to-end machine platform

Technology is only as powerful and effective as its users.

Our TEKStack AI platform draws its strength from the people that support it. Our human expertise creates applications that best leverage your data while drawing on ML technologies – this approach puts your applications ahead of what the very best have to offer. The platform accommodates an end-to-end ML lifecycle, with a particular focus on data engineering, data ingestion and pre-processing, smart data lake design, and lightweight ML pipelines. Our data journey expertise allows us to automate elements of the ML pipeline in ways that make it easier to create assets, which in turn allows us to address a greater range of customer challenges.

Enable Machine Learning
Supported by Open Source
Easy to Use
Empowered Decisions
Managed Kubeflow
User Authentication and Authorization
Knowledge Graph

Enhance your business with Enterprise Search

Search your data faster than you can think – and make data-informed insights and decisions.

TEKStack AI applies natural language processing (NLP) technologies to our enterprise search solutions, with the goal of creating faster and improved database search. This allows for context-dependent search results, more informed insights, and faster business decision-making. We first process information from the databases we ingest into our platform, then tag information based on their type (name entity recognition). We then leverage this information to produce enterprise search solutions that are easier to use, and more informative than traditional full-text search options.

Knowledge Graph
Informed Insights
More Precision in Decision Making
Big Data
Improve Performance of Recommendations

Derive greater value from your enterprise data

The right data at the right time has value greater than the sum of its parts.

TEKStack AI uses a scalable, multi-model data lake that supports any and every database best suited for the data type ingested into our platform. These databases are consolidated in a way that centralizes and simplifies data security and governance, and defines the source of truth for the datasets. The data lake is “smart”, in that it contains metadata that describes itself, which can be efficiently queried using a built-in data catalog. The data catalog allows users a greater ability to identify their data of interest across a number of different databases quickly, without the need to enlist help from a database expert.

Multi-model Data Lake
Shared Data Access
Data Governance
Real-time Analytics
Faster Decision Making
Smart Data Lake