Intuitive. Intelligent. Involving.
Intuitive.
Intelligent.
Involving.
purpose driven innovation
Technology is a tool that needs to empower, engage and delight. SLEREP delivers innovation by melding purpose, intelligence and human values at its core. Technology that optimises work without sacrificing the joy it brings.
SLEREP
customizable
Adaptable workflows designed to fit your industry’s unique needs and business goals.
intelligent
Smart data entry lets sales teams focus on customer engagement and closing deals.
insightful
Gain actionable insights on engagement, pipeline, and sales for data-driven decisions.
Mobile
Track opportunities on the go with seamless integration to Google Maps, WhatsApp, and LinkedIn.
Gamified
Turn daily tasks into challenges, compete with colleagues, and climb the leaderboard.
Powered By :
Foundation Models
Developement Tools
Driving innovation
Service-As-
Software
Past decades of automation were all about efficiency: a machine helped a human speed up a variety of tasks. The current decade is where efficiency takes an AI-fueled leap forward, and things get exponentially messier. Software once merely digitized and augmented human work and services, but in automation 2.0, bots become brains.
AI companies are leading a transition from Software-as-a-Service to Service-as-Software, turning the table on the very essence of SaaS. In the software business, a company may sell access to its platform or tool, but customers are still responsible for using that tool to achieve the desired outcome. In the services business, responsibility for achieving the desired outcome sits with the company selling the service.
Agentic Framework
Powering LLMs
The idea of “agentic” behavior in AI centers on building systems that can act with autonomy, making decisions and completing tasks with little need for human input. These AI “agents,” powered by large language models (LLMs), can understand context, generate relevant responses, and carry out actions based on set goals, enhancing both productivity and the breadth of AI-driven tasks.
One standout framework for achieving this agentic behavior is LangChain. LangChain makes it easy for developers to create LLM-powered applications by providing a modular, adaptable structure. This setup enables developers to build advanced, context-sensitive agents that can make real-time decisions and take actions on their own.
As AI progresses, frameworks like LangChain are laying the groundwork for highly capable agents that can independently tackle real-world problems.