# Helicone AI visibility in LLM Observability Evals & Gateways

Canonical: https://devtune.ai/verticals/llm-observability-evals-gateways/helicone

[Website](https://www.helicone.ai/)

Updated: 2026-10-02T02:32:07.894182+00:00
Prompts: 25
Runs: 5


## Platforms

- google-ai
- bing-copilot-search
- google-ai-mode
- perplexity
- chatgpt-search

Rank: 10
Total brands: 11
Measured responses: 125
Presence percent: 0.8
Share of voice percent: 0.4048582995951417
Average position: 1
Docs presence percent: 0.8
Blog presence percent: 0
Brand mention percent: 20


## Profile

Overview: Helicone is an open-source AI gateway and LLM observability platform launched in 2023 through Y Combinator's W23 batch. It enables AI engineers to log, monitor, debug, and analyze LLM applications via a one-line code change that routes traffic through Helicone's proxy. The platform combines a unified AI gateway—providing access to 100+ models with intelligent routing, automatic fallbacks, and response caching—with full-stack observability covering request tracing, cost and latency analytics, prompt versioning, session tracking, and evaluation scoring. Available as a managed cloud service or self-hosted via Docker or Helm, Helicone supports major providers (OpenAI, Anthropic, Azure, AWS Bedrock, Google Gemini) and frameworks (LangChain, LlamaIndex, Vercel AI SDK). In March 2026, Helicone was acquired by Mintlify and transitioned to maintenance mode.
Product summary: Helicone is an open-source LLM observability platform and AI gateway that lets developers instrument their LLM applications with a single line of code. It captures all request and response data, provides dashboards for cost, latency, and quality metrics, and acts as a multi-provider gateway supporting 100+ models with caching, fallbacks, and rate limiting. The platform is self-hostable under the Apache 2.0 license and was used by over 16,000 organizations before being acquired by Mintlify in March 2026.


### Key capabilities

- AI gateway with access to 100+ LLM models via a single OpenAI-compatible API endpoint
- One-line proxy integration by swapping the baseURL in OpenAI/Anthropic SDKs
- Real-time request logging with full prompt/response capture, latency, and token metrics
- Session and agent tracing for multi-step pipelines, chatbots, and agentic workflows
- Cost tracking and optimization including response caching and automatic fallbacks
- Prompt management with versioning, templates, and production deployment without code changes
- Evaluation scoring (Eval Scores) with dataset creation and playground for prompt experimentation
- Custom properties, user-level analytics, and HQL (Helicone Query Language) for request filtering
- Configurable rate limits, alerts, and webhook notifications
- Self-hosting support via Docker Compose and enterprise-grade Helm chart; SOC-2 Type II and GDPR compliant



### Target users

- AI/ML engineers building LLM-powered applications in production
- Full-stack developers adding generative AI features to SaaS products
- Platform and infrastructure teams managing LLM costs and reliability at scale
- AI-native startups (especially YC-backed companies) seeking lightweight LLMOps tooling
- Data scientists and prompt engineers iterating on prompt quality and fine-tuning datasets
- Enterprise teams requiring SOC-2/HIPAA compliance or on-premises LLM observability



### Key use cases

- Monitoring LLM API costs, latency, and token usage in production AI applications
- Debugging and replaying LLM requests, prompt chains, and agent sessions
- Multi-provider AI gateway routing with automatic failover and load balancing
- Prompt version management and regression testing before production deployment
- Fine-tuning data collection via curated request/response datasets
- Tracking per-user LLM spend and usage patterns for SaaS product analytics
- Enforcing rate limits and security guardrails on LLM-powered APIs
- Self-hosted LLM observability for data-sensitive or compliance-constrained environments

Integrations ecosystem: Helicone integrates natively with 15+ inference providers including OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Google Gemini (AI Studio and Vertex AI), Groq, Fireworks AI, Together AI, Anyscale, Ollama, DeepInfra, and Hyperbolic. Framework integrations include LangChain (JS/TS and Python), LlamaIndex, LangGraph, Vercel AI SDK, Semantic Kernel (C# and Python), CrewAI, MetaGPT, and ModelFusion. Analytics integrations include PostHog (for custom dashboards) and RAGAS (for RAG evaluation). Additional tool integrations include Dify, Open WebUI, Mem0 EmbedChain, Open Devin, fine-tuning partners OpenPipe and Autonomi, and an MCP server for data access. The platform also exposes a REST API and supports async logging via OpenLLMetry. Infrastructure is built on Cloudflare Workers (proxy layer), ClickHouse (analytics DB), Supabase (app DB/auth), and Minio (object storage).
Pricing summary: Free Hobby tier: 10,000 requests/month, 1 seat, 1 organization, 7-day data retention, 1 GB storage. Pro: $79/month (plus usage-based overages), unlimited seats, 1-month retention, HQL, alerts, reports, 1,000 logs/min ingestion. Team: $799/month (plus usage-based overages), 5 organizations, SOC-2 and HIPAA compliance, dedicated Slack channel, 3-month retention, 15,000 logs/min ingestion. Enterprise: custom pricing, on-prem deployment, SAML SSO, unlimited data retention, custom MSA. Usage-based pricing applies to requests and storage beyond included amounts. Discounts available for startups (<2 years old, <$5M funding: 50% off first year), non-profits, open-source projects ($100 credit), and students (free).
Review summary: Helicone has a small but consistently positive public review footprint. On G2 it holds a 4.5/5 score from 2 reviews. On Product Hunt it achieved #1 Product of the Day and draws praise for its intuitive UI, rapid integration, and responsive team. Developer sentiment highlights simplicity—the one-line setup and clean dashboard are frequently cited strengths. Criticism is sparse; one G2 reviewer noted slow upload scan performance. Community reviews emphasize the team's developer-community engagement and fast response to feature requests. No Gartner Peer Insights or Capterra scores are publicly verifiable.
Competitive positioning: Helicone positions itself as the developer-friendly, open-source alternative to LangSmith and proprietary LLM observability tools, differentiating on a one-line proxy-based integration, a combined AI gateway and observability offering, and transparent usage-based pricing with a generous free tier. The platform self-describes as the most-used LLM observability platform among YC companies and explicitly competes on open-source flexibility, provider breadth (100+ models via a single API), and an intuitive UI versus more complex enterprise competitors such as Arize AI. Gateway features (caching, fallbacks, rate limiting, multi-provider routing) are bundled natively rather than treated as a separate product, which differentiates Helicone from pure-observability peers like Langfuse and Traceloop.
Limitations: As of March 2026, Helicone entered maintenance mode following its acquisition by Mintlify, meaning no new major features are planned—only security updates, new model additions, and bug fixes. The free Hobby tier caps data retention at 7 days and ingestion at 10 logs/minute. Pro tier limits retention to 1 month. The G2 review base is very small (2 reviews), making structured user sentiment analysis unreliable. One G2 reviewer noted slow performance during file upload/scan operations. Advanced compliance features (HIPAA, SOC-2 Type II, SAML SSO) are gated to Team and Enterprise tiers. Native evaluation depth is lighter than dedicated eval platforms such as Braintrust or Galileo.


### Source urls

- https://www.helicone.ai/
- https://www.helicone.ai/pricing
- https://www.helicone.ai/blog/joining-mintlify
- https://github.com/helicone/helicone
- https://docs.helicone.ai/getting-started/quick-start
- https://www.ycombinator.com/companies/helicone
- https://www.g2.com/products/helicone/reviews
- https://www.producthunt.com/products/helicone-ai
- https://www.helicone.ai/changelog/20240829-product-hunt
- https://tracxn.com/d/companies/helicone/__Y_IYCX6RM9C6orehaoc7DBGlWaxXvHatRUYss5gZHGU

Reviewed at: 2026-05-06T17:53:55.274+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| Sunrun | Used Helicone's response caching to eliminate redundant LLM calls, reducing engineering overhead from duplicate requests. | 386 hours saved via cached responses |
| QAWolf | Leveraged Helicone's request inspection tools to accelerate debugging of LLM outputs, reducing time spent manually combing through request logs. | 2 days saved on request analysis |
| Filevine | Used Helicone to detect a critical bug in production agent workflows, enabling rapid remediation and protecting agent runtime efficiency. | 30% reduction in agent runtime saved |



### Reviews breakdown

| Platform | Score | Score max | Review count | Url |
| --- | --- | --- | --- | --- |
| G2 | 4.5 | 5 | 2 | https://www.g2.com/products/helicone/reviews |



### Review themes



#### Praised

- One-line integration simplicity
- Intuitive and clean UI dashboard
- Responsive, developer-community-driven team
- Real-time request visibility and debugging
- Effective cost and token usage tracking
- Open-source flexibility and self-hosting option
- Consistent feature rollout cadence
- Fast onboarding with no credit card required



#### Criticized

- Slow scan/upload performance (single G2 reviewer)
- Now in maintenance mode post-acquisition (no new major features)
- Advanced compliance and SSO gated to expensive tiers
- Very limited public review volume reduces signal confidence




### Company facts

Founded year: 2023
Hq: San Francisco, CA, USA


#### Founders

- Justin Torre
- Cole Gottdank
- Scott Nguyen

Employees range: 2-10
Total funding: $1.5M
Valuation: Not available
Arr: Not available
Customer count: 16,000+ organizations
Status: Acquired by Mintlify (Mar 2026), maintenance mode


Readiness: Not available


## Ranking

| Display name | Pair count | Total pairs | Presence percent | Avg position |
| --- | --- | --- | --- | --- |
| Arize AI | 36 | 125 | 28.799999999999997 | 3.30188679245283 |
| Langfuse | 32 | 125 | 25.6 | 2.5106382978723403 |
| Braintrust | 28 | 125 | 22.400000000000002 | 2.58974358974359 |
| LangChain | 27 | 125 | 21.6 | 3.311111111111111 |
| LiteLLM | 12 | 125 | 9.6 | 2.611111111111111 |
| Portkey | 10 | 125 | 8 | 2.3076923076923075 |
| Galileo | 7 | 125 | 5.6000000000000005 | 4.3 |
| Confident AI | 6 | 125 | 4.8 | 3.4 |
| Traceloop | 3 | 125 | 2.4 | 4.2 |
| Helicone | 1 | 125 | 0.8 | 1 |
| Patronus AI | 1 | 125 | 0.8 | 1 |



## Platform breakdown

| Platform | Prompt count | Presence rate |
| --- | --- | --- |
| google-ai | 0 | 0 |
| bing-copilot-search | 0 | 0 |
| google-ai-mode | 0 | 0 |
| perplexity | 1 | 4 |
| chatgpt-search | 0 | 0 |



## Strengths

| Prompt text | Platform count | Avg position |
| --- | --- | --- |
| Which LLM gateway tools give developers the best real-time cost and token usage visibility across multiple LLM providers during development? | 1 | 1 |



## Gaps

| Prompt text | Competitor presence count |
| --- | --- |
| What platforms support end-to-end tracing of multi-agent pipelines including tool calls, retrieval steps, and sub-agent spawning? | 5 |
| Looking for an eval platform that supports automated safety and toxicity scoring on LLM outputs at scale — what are my options? | 5 |
| I'm looking for an LLM observability platform with a great team collaboration workflow — where engineers and PMs can both review trace quality without SQL knowledge. | 4 |
| What LLM tracing platforms handle high-throughput production workloads — millions of traces per day — without degrading query performance? | 4 |
| Which LLM eval platforms support async evaluation at scale without blocking the inference path or adding latency for end users? | 4 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 0 |
| Developer Experience | 5 | 1 |
| Integrations & Ecosystem | 5 | 0 |
| Performance & Reliability | 5 | 0 |
| Setup & First Run | 5 | 0 |



## Prompt results

- Prompt text: I'm looking for an LLM observability platform with a great team collaboration workflow — where engineers and PMs can both review trace quality without SQL knowledge.


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Confident AI | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Langfuse | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 3 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |


- Prompt text: What are the best OpenTelemetry-compatible tracing backends for LLM apps that work out of the box without custom span parsing?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Langfuse | 5 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LangChain | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Arize AI | 1 |
| Traceloop | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |


- Prompt text: Which LLM observability tools handle PII redaction and data masking in traces for teams with HIPAA or GDPR compliance requirements?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Portkey | 2 |
| Arize AI | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Langfuse | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |
| LangChain | 3 |


- Prompt text: Which LLM observability tools work with OpenTelemetry-compatible backends so we can consolidate LLM traces alongside existing service traces?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Traceloop | 7 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Braintrust | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |
| LangChain | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Arize AI | 2 |


- Prompt text: What platforms support end-to-end tracing of multi-agent pipelines including tool calls, retrieval steps, and sub-agent spawning?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Langfuse | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Braintrust | 2 |
| Arize AI | 3 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Arize AI | 1 |
| LangChain | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| LangChain | 1 |
| Langfuse | 4 |
| Arize AI | 6 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |
| Braintrust | 3 |


- Prompt text: What LLM tracing platforms handle high-throughput production workloads — millions of traces per day — without degrading query performance?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Braintrust | 1 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Galileo | 1 |
| Braintrust | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 5 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 3 |


- Prompt text: Which LLM eval platforms support async evaluation at scale without blocking the inference path or adding latency for end users?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Arize AI | 3 |
| Galileo | 4 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| Arize AI | 2 |
| Langfuse | 3 |
| LangChain | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Arize AI | 1 |


- Prompt text: Which LLM observability platforms stay reliable under traffic spikes from batch eval jobs running thousands of LLM calls simultaneously?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| Galileo | 2 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| LangChain | 2 |
| Langfuse | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| Langfuse | 3 |
| LangChain | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |
| Braintrust | 3 |


- Prompt text: Which LLM gateways handle multi-provider fallback and automatic retries while preserving full trace context across the switch?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Portkey | 1 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |
| LangChain | 2 |
| Portkey | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| LiteLLM | 2 |



##### Chatgpt-search




- Prompt text: What's the fastest LLM tracing platform for instrumenting a Python-based agent framework without rewriting existing code?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Confident AI | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Arize AI | 2 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 2 |


- Prompt text: I'm evaluating LLM gateway solutions for a startup — which ones have the simplest self-hosted setup with a working UI on day one?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Arize AI | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |
| Portkey | 4 |



##### Chatgpt-search




- Prompt text: Which evaluation platforms for LLM outputs are easiest to plug into an existing CI pipeline for a five-engineer team?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Braintrust | 6 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Confident AI | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Braintrust | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Braintrust | 3 |
| LangChain | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Braintrust | 3 |
| Langfuse | 4 |


- Prompt text: What are the most production-hardened LLM gateway options for an enterprise team needing 99.9% uptime with circuit-breaker support?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Braintrust | 4 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Portkey | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Arize AI | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Portkey | 2 |
| LiteLLM | 3 |


- Prompt text: Which LLM observability platforms can a small team get running against a production RAG pipeline in under a day?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Galileo | 2 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LangChain | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| LangChain | 1 |
| Langfuse | 3 |
| Arize AI | 6 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Arize AI | 1 |
| LangChain | 2 |


- Prompt text: Which LLM tracing platforms make it easiest to replay a failed multi-step agent run and pinpoint exactly where reasoning went wrong?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Braintrust | 1 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Braintrust | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| LangChain | 1 |
| Langfuse | 3 |
| Arize AI | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Arize AI | 1 |


- Prompt text: Which LLM tracing platforms export trace data to a data warehouse so analysts can run custom eval queries alongside product metrics?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| LangChain | 1 |
| Langfuse | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Confident AI | 4 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| LangChain | 2 |



##### Perplexity





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Arize AI | 1 |
| Braintrust | 2 |
| LangChain | 3 |


- Prompt text: Which LLM gateways add the least latency overhead when routing between LLM providers — safe to use in production for sub-500ms SLAs?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| LiteLLM | 2 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |
| Portkey | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |



##### Chatgpt-search




- Prompt text: What LLM gateway tools integrate best with secret managers and internal auth systems for enterprise teams rolling out to multiple product teams?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |
| Portkey | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Portkey | 1 |
| LiteLLM | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| LiteLLM | 1 |
| Portkey | 4 |


- Prompt text: Which LLM eval platforms have the best prompt playground experience for iterating on system prompts against a saved test dataset?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Langfuse | 4 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Confident AI | 5 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Traceloop | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| LangChain | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| LangChain | 1 |
| Arize AI | 2 |
| Braintrust | 4 |


- Prompt text: Which LLM evaluation platforms support custom rubric-based scoring for domain-specific correctness beyond generic faithfulness metrics?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Arize AI | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| LangChain | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| LangChain | 1 |
| Braintrust | 2 |
| Arize AI | 3 |
| Langfuse | 4 |


- Prompt text: Which LLM gateway tools give developers the best real-time cost and token usage visibility across multiple LLM providers during development?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: 1
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Langfuse | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Helicone | 1 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |


- Prompt text: Looking for an eval platform that supports automated safety and toxicity scoring on LLM outputs at scale — what are my options?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai

| Display name | Position |
| --- | --- |
| Braintrust | 2 |
| Galileo | 3 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Galileo | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LangChain | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Arize AI | 1 |
| Galileo | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Patronus AI | 1 |
| Arize AI | 2 |
| Braintrust | 3 |
| LangChain | 4 |


- Prompt text: Which LLM observability platforms integrate natively with the most popular agent frameworks so traces appear automatically with no manual instrumentation?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 3 |
| LangChain | 5 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 3 |
| Braintrust | 4 |


- Prompt text: What LLM observability tools do ML engineering teams typically use to annotate and review production traces for quality feedback?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LangChain | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Langfuse | 1 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Langfuse | 1 |
| Arize AI | 2 |


- Prompt text: I'm evaluating LLM eval platforms — which ones integrate with version control to tie prompt regressions back to specific code or config changes?


#### Brand position by platform

Google-ai: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Perplexity: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Confident AI | 1 |
| Braintrust | 3 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| LiteLLM | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| LangChain | 2 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| LangChain | 3 |
| Arize AI | 4 |





## Top sources

| Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count |
| --- | --- | --- | --- | --- | --- | --- | --- |
| https://docs.helicone.ai/guides/cookbooks/cost-tracking | Cost Tracking & Optimization - Helicone OSS LLM Observability | docs.helicone.ai | Not available | commercial | documentation | 1 | 1 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| What platforms support end-to-end tracing of multi-agent pipelines including tool calls, retrieval steps, and sub-agent spawning? | bing-copilot-search | Leading options include MLflow, Braintrust, LangSmith, Langfuse, Helicone, Arize AX/Phoenix, and Galileo AI. 🔑 Key Platforms for Multi-Agent Tracing ---------------------------------------- \| Platform \| Strengths \| Deployment Model \| Best Fit Use C... |
| What LLM tracing platforms handle high-throughput production workloads — millions of traces per day — without degrading query performance? | bing-copilot-search | The 7 Best LLM Observability and Tracing Tools in 2026: Langfuse, LangSmith, Arize, Helicone, Braintrust, Weave, and TrueFoundry Compared \| \| Langfuse \| Fully open-source, MIT license, strong prompt management, evaluation integration \| Self-hosted o... |
| Which LLM observability platforms stay reliable under traffic spikes from batch eval jobs running thousands of LLM calls simultaneously? | bing-copilot-search | Proxy-based tools (e.g., Helicone) add a network hop, which can bottleneck under spikes. |



## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| google-ai | Langfuse | Langfuse * Best For: Open-source flexibility, self-hosting, and cost-effective production scaling. |
| bing-copilot-search | Braintrust | Leading options include MLflow, Braintrust, LangSmith, Langfuse, Helicone, Arize AX/Phoenix, and Galileo AI. 🔑 Key Platforms for Multi-Agent Tracing ---------------------------------------- \| Platform \| Strengths \| Deployment Model \| Best Fit Use C... |
| google-ai-mode | Arize AI | Arize AI +1 * * * If you'd like to narrow this down, tell me: * Are you looking for an open-source/self-hosted tool or a fully managed SaaS platform? |
| google-ai-mode | LangChain | The Experience: LangChain’s platform features a robust "Test over dataset" workflow directly inside the web playground. |
| chatgpt-search | Langfuse | ...\| Tool calls \| Retrieval / RAG \| Cross-service tracing \| OpenTelemetry \| \| --- \| --- \| --- \| --- \| --- \| --- \| \| Langfuse \| Yes \| Yes \| Yes \| Yes \| Yes \| \| Arize Phoenix \| Yes \| Yes \| Yes \| Yes \| Yes*... |
| chatgpt-search | Braintrust | ...\| Yes \| Yes \| Yes \| Yes \| \| Arize Phoenix \| Yes \| Yes \| Yes \| Yes \| Yes \| \| Braintrust \| Yes \| Yes \| Yes \| Yes \| Yes \| \| LangSmith \| Yes \| Yes \| Yes \| Yes \| Yes \| \| *... |
| google-ai | Braintrust | Braintrust: www.braintrust.dev * Best for: Enterprise-grade tracking, automated scoring, and dataset management. |
| google-ai | Galileo | Galileo: * Best for: Real-time data monitoring and deep safety/toxicity evaluation. |
| bing-copilot-search | Galileo | The strongest options for automated safety and toxicity scoring of LLM outputs at scale include Galileo, ModelBench (MLCommons), ForesightSafety-SAGE, and specialized frameworks like SafePro and VERA-MH. |
| google-ai-mode | LangChain | Docs by LangChain +1 * Braintrust : Features LLM-based Scorers letting you define custom judge prompts equipped with explicit rubrics, chain-of-thought reasoning, and custom choice-to-score mappings designed for subjective or expert professional domains. |
| chatgpt-search | Patronus AI | ...Safety/toxicity \| Production/online evals \| Scale / workflow \| Self-hosting \| \| --- \| --- \| --- \| --- \| --- \| \| Patronus AI \| Strong — dedicated toxicity and safety evaluators \| Yes \| Experiments, logs, datasets, comparisons \| Enterprise... |
| chatgpt-search | Braintrust | ...tomizable evaluators \| Yes \| Span/trace/session evals, observability \| Phoenix is open-source/self-hostable \| \| Braintrust \| Custom safety/LLM-as-judge scorers \| Yes \| Datasets → experiments → production traces → CI/CD \| BYOC/self-hosting... |



## Trend

Visibility delta: -0.6000000000000001
Avg position delta: -1.5
Citation count delta: -1