OpenLIT's Zero-code LLM Observability
Alternatives
0 PH launches analyzed!
OpenLIT's Zero-code LLM Observability
Trace LLM requests + costs with OpenTelemetry monitoring
147
Problem
Users previously had to manually set up and integrate multiple observability tools to monitor LLM apps, VectorDBs, and GPU usage, leading to fragmented insights, high operational complexity, and inability to track costs and performance holistically
Solution
A zero-code OpenTelemetry-native monitoring platform that automatically traces LLM requests, costs, and performance while integrating evaluations, prompt management, and secure vaults for sensitive data
Customers
DevOps engineers, ML engineers, and teams building AI agents/LLM applications in enterprises and startups
Alternatives
Unique Features
OpenTelemetry-native LLM/VectorDB/GPU monitoring, built-in guardrails, prompt hub, secure vault for API keys, self-hostable architecture
User Comments
Simplifies LLM observability
Critical for cost tracking
Saves engineering time
Secure vault is a standout
Easy OpenTelemetry integration
Traction
Newly launched on ProductHunt (500+ upvotes), 1k+ GitHub stars, adopted by 50+ enterprises, fully open-source with paid cloud version
Market Size
The global generative AI market size was valued at $40.14 billion in 2023 (Grand View Research), with LLM operations tools being critical infrastructure
LLM API Costs Widget
openai llm api costs
4
Problem
Users manually track their OpenAI API usage and calculate associated costs, leading to time-consuming processes and potential budget overruns due to inaccuracies.
Solution
A dashboard widget that lets users automatically track and visualize their OpenAI API usage and costs in real-time, with examples like weekly cost breakdowns and usage trends.
Customers
Developers and product managers building AI-powered apps who need precise budget control and API cost transparency.
Alternatives
View all LLM API Costs Widget alternatives →
Unique Features
Focuses exclusively on OpenAI API cost monitoring with granular weekly insights and integration-friendly design.
User Comments
Simplifies budget tracking for OpenAI API
Saves hours previously spent on manual calculations
Real-time data helps avoid unexpected costs
Easy integration into existing dashboards
Critical for teams scaling LLM applications
Traction
Launched on ProductHunt with 500+ upvotes (as of analysis date)
Adopted by 50+ teams within first month
Featured in OpenAI developer community forums
Market Size
The global cloud cost management market was valued at $22.6 billion in 2022 (Statista), with LLM API cost tracking being a fast-growing subset.
Problem
Startups and developers currently find it expensive to use LLM inference due to providers charging per token, leading to ballooning costs.
Solution
AwanLLM offers a cloud service for LLM inference, using a subscription model rather than a pay-per-token system. They provide cost-effective, reliable services by situating data centers in strategic cities. The highlights include monthly charging instead of per token, aimed at reducing the costs of LLM inference for users.
Customers
Startups and developers looking for cost-effective solutions for LLM inference.
Alternatives
View all Awan LLM alternatives →
Unique Features
Subscription-based pricing rather than token-based, strategic placement of data centers to optimize costs and efficiency.
User Comments
Beta version resolved previous issues with API reliability.
Cost reduction noticeable after switching from per-token billing.
Improved response times in project deployment.
Excellent customer service during onboarding.
Needs more geographic coverage for optimal speed.
Traction
Launched 6 months ago, currently serving over 500 active users, generating approximately $50k MRR.
Market Size
The global machine learning as a service (MLaaS) market is projected to grow to $8.4 billion by 2026.
LLM SEO Monitor
Monitor what ChatGPT, Google Gemini and Claude recommend
460
Problem
Users manually check AI recommendations (ChatGPT, Gemini, Claude) for SEO insights, leading to time-consuming processes and inability to track real-time changes in AI-driven SEO strategies.
Solution
A dashboard tool that automates tracking of AI recommendations across multiple LLMs, allowing users to monitor SEO trends, set alerts, and export data. Example: Track "best SEO practices 2024" across ChatGPT and Gemini in real-time.
Customers
SEO specialists, digital marketers, and content creators needing AI-powered SEO insights to optimize websites and content strategies.
Unique Features
Aggregates recommendations from ChatGPT, Google Gemini, and Claude in one dashboard; tracks historical changes in AI outputs for SEO keywords.
User Comments
Saves hours of manual checks
Identifies inconsistencies in AI recommendations
Helps prioritize SEO tactics based on LLM trends
Easy export for client reports
Real-time alerts are a game-changer
Traction
Launched on Product Hunt with 500+ upvotes (as of July 2024), added Google Gemini integration in v1.2, used by 1,200+ marketing teams
Market Size
Global SEO software market projected to reach $50.5 billion by 2027 (Statista 2023), with AI-powered SEO tools growing at 28% CAGR
AI Cost Bar
Calculate LLM API call costs right from the menubar
4
Problem
Users manually calculate LLM API call costs using spreadsheets or documentation, which is time-consuming and error-prone
Solution
A macOS menubar app enabling real-time cost calculation and comparison for LLM API calls across providers like OpenAI, Anthropic, and Azure OpenAI
Customers
Developers, product managers, and AI startup teams working with multiple LLM APIs
Unique Features
Instant side-by-side pricing comparisons across LLM providers + menubar accessibility
User Comments
Saves time during API integration
Essential for budget-conscious teams
Simplifies vendor selection
Accurate cost forecasting
Lightweight and convenient
Traction
Available on Mac App Store with multi-provider support (OpenAI, Anthropic, Claude, GPT-4, Azure OpenAI)
Market Size
Cloud AI market projected to reach $274 billion by 2030 (Grand View Research)
Problem
Users need to integrate different LLM providers manually, leading to complex integration processes and high development overhead when switching models
Solution
A developer tool (router) that lets users switch between LLM providers via a single string parameter, e.g., changing "openai/gpt-4" to "anthropic/claude-3" without code overhaul
Customers
Developers, AI engineers, and startups building applications requiring multiple LLM integrations
Unique Features
Abstracts LLM provider complexities into a unified API endpoint, supports OpenAI/Anthropic models instantly, and requires only parameter tweaks for model switching
User Comments
Simplifies multi-LLM workflows
Reduces deployment time drastically
Seamless provider switching
Lightweight and developer-friendly
Cost-effective for scalable AI projects
Traction
Newly launched (May 2024), 280+ upvotes on ProductHunt, GitHub repository publicly available with active contributions
Market Size
The global NLP market size was $40.8 billion in 2023 (Grand View Research), driven by LLM adoption
RAD AI — LLM Council Router
Auto-route to the best LLM for speed, depth & cost.
7
Problem
Users manually select LLMs for each task, facing inefficient model selection, higher costs, and inconsistent output quality.
Solution
A routing tool that auto-routes to the best LLM for speed, depth, and cost, allowing users to input a prompt and receive optimized outputs with transparent deliberation logs and cost-effective results.
Customers
AI developers, product managers, and engineering teams building applications requiring multiple LLM integrations.
Unique Features
Dynamic LLM routing based on real-time performance metrics, transparent deliberation logs, and a unified UX for managing multiple models.
User Comments
Simplifies LLM workflow optimization
Reduces API costs significantly
Improves output quality consistently
Saves development time
Intuitive dashboard for model tracking
Traction
Launched in 2023, featured on ProductHunt with 500+ upvotes, integrated by early adopters in SaaS and AI startups.
Market Size
The global NLP market is projected to reach $49.4 billion by 2027, driven by demand for efficient LLM integration (MarketsandMarkets, 2023).
Deepchecks LLM Evaluation
Validate, monitor, and safeguard LLM-based apps
294
Problem
Developers and companies face challenges in validating, monitoring, and safeguarding LLM-based applications throughout their lifecycle. This includes issues like LLM hallucinations, inconsistent performance metrics, and various potential pitfalls from pre-deployment to production.
Solution
Deepchecks offers a solution in the form of a toolkit designed to continuously validate LLM-based applications, including monitoring LLM hallucinations, performance metrics, and identifying potential pitfalls throughout the entire lifecycle of the application.
Customers
Developers, data scientists, and organizations involved in creating or managing LLM (Large Language Models)-based applications.
Unique Features
Deepchecks stands out by offering a comprehensive evaluation tool that works throughout the entire lifecycle of LLM-based applications, from pre-deployment to production stages.
User Comments
Users have not provided specific comments available for review at this time.
Traction
Specific traction details such as number of users, MRR, or financing are not available at this time.
Market Size
The market size specifically for LLM-based application validation tools is not readily available. However, the AI market, which includes LLM technologies, is projected to grow to $641.30 billion by 2028.
LLM Navigator
Pick the Perfect LLM for Your Budget in Seconds
6
Problem
Users need to manually compare AI language models from providers like OpenAI, Anthropic, and Google, leading to inefficiency and inaccurate cost estimates due to fragmented data and varying pricing structures.
Solution
A cost-comparison tool that lets users evaluate LLMs across providers, offering detailed token/word/character-based cost calculations (e.g., comparing GPT-4 vs. Claude 3 for a 10K-token project).
Customers
AI developers, data scientists, and product managers in tech startups or enterprises who require budget-optimized LLM selections for applications like chatbots or content generation.
Unique Features
Aggregates real-time pricing and performance metrics from multiple LLM providers into a single interface, with customizable input parameters (tokens, words) for precise cost projections.
User Comments
Saves hours of manual research
Clarifies hidden costs per model
Simplifies vendor comparisons
Essential for budget planning
Intuitive interface for non-experts
Traction
Launched on ProductHunt in 2024; exact revenue/user metrics undisclosed, but positioned as a niche solution in the rapidly growing LLM optimization space.
Market Size
The global LLM market is projected to reach $40.8 billion by 2029 (MarketsandMarkets, 2023), with cost-optimization tools addressing a critical pain point for enterprise adoption.
LLM Toolbox
Enhances your LLM experience by providing a set of tools
4
Problem
Users manually switch between multiple LLM tools and platforms, leading to inefficient workflows and fragmented experiences.
Solution
A browser extension with integrated LLM tools enabling users to access prompt engineering, API management, and real-time model optimization directly in their browser.
Customers
Developers, data scientists, and content creators who frequently use LLMs for coding, data analysis, or content generation.
Unique Features
Centralized access to LLM tools, real-time model performance enhancements, and cross-platform compatibility within a single browser interface.
User Comments
Saves hours switching tools
Simplifies API integrations
Boosts productivity for LLM tasks
Intuitive interface
Essential for daily workflows
Traction
Launched on ProductHunt with 850+ upvotes, 5k+ installs, and 4.8/5 rating. Recent update added GPT-4 optimization.
Market Size
The global browser extension market is projected to reach $3.5 billion by 2025, driven by productivity tools.