Guickly

Website

Guickly, Inc.

2 Investors
Large Language Model Development
SAN JOSE, CA

Guickly, Inc. is an artificial intelligence and machine learning software company that provides a self-serve platform for rapid large language model (LLM) fine-tuning, training, and deployment. Founded by ex-Googlers, the company focuses on automating complex AI workflows to help enterprises create and launch custom, production-ready language models quickly and efficiently.

Products & Team

Self-Serve LLM Fine-Tuning Platform

SaaS PlatformSeed

A Software-as-a-Service (SaaS) platform that enables organizations to launch custom, production-ready LLMs in days instead of weeks. It automates the entire development lifecycle, from model selection and parameter tuning to deployment and ongoing maintenance, allowing for quick integration of fine-tuned models tailored to specific company data.

Value Proposition

The platform solves the problem of lengthy, error-prone, and costly legacy workflows in custom AI model development by providing a fast, automated, and cost-effective solution for enterprises to deploy tailored LLMs.

Pain Points

Customers face challenges with long deployment timelines, high API costs, model latency, poor model accuracy, and complex, error-prone development processes associated with traditional LLM fine-tuning.

Agentic AI Automation for model selection and parameter tuningInstant setup and one-click deployment capabilitiesSignificant API cost reduction compared to legacy workflowsAutomated data drift management and model retrainingCompatibility with open-source and commercial models like LLaMA, Mistral, and DeepSeekDirect integration with existing Gemini, OpenAI, and Anthropic API callsSecure, isolated sandbox architecture for each customer with data encryption
Industry
Other Technology
Primary business sector
Founded
2025
Year established
Location
SAN JOSE, CA
Primary headquarters

Funding History

Total Raised:
$3.5M
E

Equity Offering

November 2025
$5.0M
Target
Progress
70%
Raised
$3.5M
Target
$5.0M
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