SERVICE PROVIDED: STAFF Augmentation

Secure and compliant AI management

Kindo centralizes access to diverse AI models, including private, commercial, and open source, fostering workforce productivity with a unified interface and seamless integration with 200+ SaaS platforms.

https://kindo.ai/

Node
Prisma
React
Next
Redis
AWS

THE CLIENT

Kindo is a forward-thinking startup operating in the AI sector, specializing in Large Language Models (LLMs) like ChatGPT and cloud technologies.

Dedicated to making AI accessible to businesses, the company offers a SaaS solution that integrates seamlessly with various platforms, including Dropbox, Google Drive, Jira, Linear, accounting software, CRM tools, and more—all supported by merge.dev.

The company sought our expertise in staff augmentation to enhance their front-end and back-end development capabilities.

The Challenge

Initially, the client’s need for a front-end developer focused on React Native mobile development marked the commencement of our collaboration.

Beyond this, the challenges expanded into the intricate realm of backend development, necessitating the incorporation of advanced Large Language Models (LLMs) like gpt4, gpt3, claude 100k, claude v2, claude Instant, falcon, and palm. The integration of these LLMs was pivotal for the client’s objective of making AI accessible to businesses through their SaaS offering.

To enhance the AI capabilities, our team delved into improving data organization and embeddings, adopting technologies such as Pinecone Store for efficient storage and retrieval of embeddings. The introduction of a synchronized background worker became imperative to pick up real-time changes in documents from platforms like Dropbox, Google Drive, and various ticketing systems. This worker tokenized and embedded each new or modified item, creating a dynamic index for the LLMs to gain context as per user requests.

The challenges were multifaceted, ranging from enhancing AI capabilities through LLM integrations to optimizing data organization, embedding mechanisms, and token balance management. The technical intricacies involved advanced technologies and a meticulous approach to ensure the seamless integration of diverse systems and the successful delivery of an advanced AI solution.

Some of our services included:

RESULTS

Our comprehensive approach resulted in a streamlined and efficient system. To overcome the multiple challenges, we implemented a series of solutions.

We created alarms and metrics using DataDog to visualize events and metrics effectively. All environment variable management was streamlined into Doppler for enhanced configuration management. An embedding mechanism utilizing Pinecone Store was introduced, and a synchronized background worker was developed to tokenize and embed changes in documents, tickets, and CRM entries, making them readily available for the LLM. 

The token balance system using Redis streams and hashes provided an effective solution for managing user token usage, aligning with different plans and ensuring daily refills and initial balances.

More of our work

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