Helicone AI
Langfuse
LangSmith
Portkey
liteLLM
LangChain
OpenRouter
Openlayer
AWS Lambda
Amazon API Gateway
Amazon S3
Google App Engine
DynamoDB
Google Cloud Functions
Amazon AWS
AWS Elastic Beanstalk
Helicone AI
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Based on our record, AWS Lambda seems to be a lot more popular than Helicone AI. While we know about 297 links to AWS Lambda, we've tracked only 5 mentions of Helicone AI. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Helicone takes the simplest possible approach to LLM monitoring: it's a proxy. Change your OpenAI base URL from api.openai.com to oai.helicone.ai, add your Helicone API key as a header, and every LLM request is logged โ latency, tokens, cost, prompts, and completions. No SDK integration, no code changes beyond a URL swap. - Source: dev.to / 19 days ago
You're monitoring production traffic. You need Langfuse / Phoenix / Helicone / Braintrust for that. Online eval is a different problem class: implicit feedback, drift detection, hallucination rates on your data, not on HellaSwag. - Source: dev.to / 29 days ago
For many teams, especially those starting out or with simpler needs, commercial solutions like Portkey, Helicone, OpenPipe, or LiteLLM Proxy offer off-the-shelf capabilities that cover many common proxy use cases (caching, logging, cost tracking). NeuroLink itself can be seen as an SDK that complements these, allowing you to integrate with them or build similar features on top. - Source: dev.to / 3 months ago
TL;DR: Go with Langfuse if you want open-source and self-hosted. Pick Helicone if you want the fastest setup (2 minutes, no SDK). Stick with LangSmith if your stack already runs on LangChain. And if your org already pays for Datadog, their LLM module slots right in. - Source: dev.to / 4 months ago
Hey HN, we're Justin and Cole, the founders of Helicone (https://helicone.ai) or self-deploy with our new fully open-source helm chart (https://helicone.ai/selfhost). Yet even with detailed traces, probabilistic systems are notoriously hard to debug at scale. So, we released evaluators (either via LLM-as-judge or custom Python evaluators leveraging the CodeSandbox SDK - https://codesandbox.io/docs/sdk/sandboxes).... - Source: Hacker News / over 1 year ago
AWS Lambda is a service that runs your code without you managing any servers. You write your code, deploy it to Lambda, and it takes care of the infrastructure โ servers, networking, security, and scaling. - Source: dev.to / about 2 months ago
Clay can replace the Lambda and API chain if you'd rather avoid custom code. You set up a Clay table as the enrichment layer, trigger it from Segment via webhook, and it handles the waterfall and CRM push without writing a function. The tradeoff: less control over scoring logic and higher cost per enriched contact. - Source: dev.to / about 1 month ago
To show why this matters, take a look at the following example. I have three AWS Lambda functions, Lambda being the serverless compute service, that each handle a different endpoint on the same API. But, almost everything about them is the same. They have the same runtime, the same memory configuration, and nearly the same structure. The only differences are the name, handler, and possibly some environment variables. - Source: dev.to / about 1 month ago
Query Expansion and Decomposition: Amazon Bedrock query expansion broadens search; AWS Lambda query decomposition breaks complex queries into sub-queries; AWS Step Functions orchestrates multi-step retrieval. - Source: dev.to / 2 months ago
You need to understand synchronous and asynchronous inference patterns, event-driven architectures using Amazon EventBridge, workflow orchestration with AWS Step Functions, data processing with AWS Lambda, state management with Amazon DynamoDB, and security with AWS Identity and Access Management (IAM). The exam tests your ability to design serverless architectures that scale automatically, handle failures... - Source: dev.to / 3 months ago
Langfuse - Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.
Amazon API Gateway - Create, publish, maintain, monitor, and secure APIs at any scale
LangSmith - Build and deploy LLM applications with confidence
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.
Portkey - Build production-grade & reliable AI apps with Portkey
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.