Use AI to Scale, Innovate and Stay Ahead of Your Competitors
Enter the new age of intelligence and lead the market with our AI services. We aid businesses in embedding the power of AI and improving their performance through seasoned AI developers.
We can now deliver performance efficiencies you can easily measure with AI and ML delivered as part of our IaaS model.
Enhance efficiency & accuracy
Focus on more valuable job aspects
Extract more accurate and valuable insights
Gain a huge competitive edge
Competitive Edge
Better User Experience
Automation Advantage
Valuable Insights
Our Process for AI and ML Implementation
Blueprint
We engineer practical data-driven algorithms to implement machine learning solutions for businesses by separating the AI hype from computational realities.
Delivery
Ultimately, we package the solution with built-in compatibility for the most popular delivery systems to enable easy, flexible, and convenient operations capabilities at the enterprise scale.
Fabricate
Our team then assembles the components together via intelligent automation. This enables us to dramatically accelerate initial solution delivery as well as maintenance concerns and ongoing operations.
Baseline
The Abaca team then works towards prefabricating components that implement the reference architecture. A plethora of ready-to-use options are available for each reference architecture component, thereby benefiting clients from innovation.
Our Services
Future-ready Solutions
AI-Driven Processes
Let our team help you build a competitive advantage in your industry. We strive to integrate artificial intelligence and machine learning into your business processes. Our powerful systems are focused on readiness, innovation, and outcome effectiveness.
Custom AI-Driven Solutions
We offer you the full spectrum of artificial intelligence solutions. From augmented operations to collaborative intelligence, our team strives to deliver custom-built AI solutions. We can help you accelerate your business operations.
Data Processing
Expect us to help you build robust and scalable data infrastructures for your AI/ML systems. Our team at Abaca will help you implement a comprehensive data culture that covers all processes including data collection, data mining, and data aggregation.
Machine Learning
Have your current implementation tested and assembled by the most proficient AI and ML engineers. We can also help you design a custom machine learning model for your company. With us, you can rest assured of the reliability and accuracy of your ML model.
Human-to-machine &
Machine-to-machine
We design, develop, and implement machine-to-machine and human-to-machine AI solutions for creating interactive, flexible, and secure automated processes. Embrace programmed decision-making, digital assistants, voice recognition, and intention recognition.
Deep Learning
Technologies
Let our cutting-edge technologies driven by AI augment the capabilities of your business, employees, products, services, and processes. Fraud detection, anomaly detection, face detection, medical diagnosis, and demand prediction are some of the processes included.
How Do You Want Us to Transform Your Business?
Frequently Asked
Questions
Artificial intelligence refers to the simulation of human intelligence processes by machines including robots and computer systems. Most of the specific applications of AI include natural language processing, speech recognition, machine vision, and expert systems.
Yes, they certainly can. In fact, modern AI is based on Machine Learning. The latter is a category of computer algorithms that can automatically learn from data, instead of depending on humans to program each step. ML is a subset of artificial intelligence.
Machine learning algorithms can be broadly categorized into 3 types:
AI projects can take anywhere from a few months to a year to go live, depending on their scope and complexity. It is advised not to underestimate the time it takes to prepare the data before a data science engineer builds an AI algorithm
In AI, the biggest challenges are power efficiency, learning from less data, learning from unlabeled data (unsupervised learning), and generalizing across multiple tasks. In addition to making AI unbiased and explainable, the industry also aims to quantify confidence levels and understand how it works. It would be interesting to understand how AI used for autonomous driving decides how to drive safely on a road in a variety of environments and weather conditions.