# LiteLLM AI visibility in LLM Observability Evals & Gateways

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

[Website](https://litellm.ai/)

Updated: 2026-10-01T12:06:12.44521+00:00
Prompts: 25
Runs: 5


## Platforms

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

Rank: 5
Total brands: 11
Measured responses: 125
Presence percent: 8.799999999999999
Share of voice percent: 7.905138339920949
Average position: 2.9
Docs presence percent: 7.199999999999999
Blog presence percent: 0
Brand mention percent: 0


## Profile

Overview: BerriAI's LiteLLM is an open-source AI Gateway and Python SDK that provides a single, unified, OpenAI-compatible interface for calling 100+ large language model (LLM) providers, including OpenAI, Anthropic, Azure, AWS Bedrock, Google Vertex AI, Cohere, and Mistral. Founded in 2023 and backed by Y Combinator (W23), LiteLLM is offered both as a lightweight Python library for developers and as a self-hosted proxy server for platform teams managing LLM access across organizations. Core capabilities include multi-provider load balancing and fallbacks, virtual key management, per-user/team/org spend tracking, rate limiting, LLM guardrails, and observability integrations. With over 45,000 GitHub stars, 240 million Docker pulls, and 1 billion requests served, it is one of the most widely adopted open-source LLM infrastructure tools.
Product summary: LiteLLM (by BerriAI) is an open-source AI Gateway and Python SDK that standardizes access to 100+ LLM providers under a single OpenAI-format API. It can be used as an embedded Python library or deployed as a standalone FastAPI proxy server with virtual keys, spend tracking, guardrails, load balancing, observability integrations, and an admin dashboard — enabling platform teams to give developers governed LLM access at scale.


### Key capabilities

- Unified OpenAI-format API across 100+ LLM providers
- AI Gateway / Proxy Server with virtual keys and admin dashboard UI
- Spend tracking and budget enforcement per user, team, org, and tag
- Load balancing and automatic fallbacks across LLM deployments
- LLM guardrails for content filtering and PII masking
- Rate limiting and per-key/team/project quota management
- LLM observability via OpenTelemetry, Langfuse, Arize, and others
- MCP (Model Context Protocol) Gateway for tool-augmented LLM calls
- A2A Agent Gateway supporting multi-agent protocol routing
- 8ms P95 latency at 1,000 RPS (self-reported benchmark)



### Target users

- ML platform and GenAI enablement teams managing LLM access at scale
- Backend and AI engineers building multi-provider LLM applications
- Enterprise AI infrastructure architects in regulated industries
- DevOps and platform engineers deploying self-hosted LLM gateways
- AI startup developers seeking provider-agnostic LLM abstraction
- Security and compliance teams requiring auditable LLM access controls



### Key use cases

- Platform and ML teams providing centralized LLM access to large developer organizations
- Multi-provider LLM routing with automatic failover for production reliability
- Cross-provider cost tracking and AI budget governance
- Self-hosted LLM gateway for regulated or air-gapped environments
- Day-0 model access enablement when new LLM providers launch
- Standardizing LLM API calls across heterogeneous provider stacks
- Centralized prompt management and observability logging
- MCP and A2A agent traffic routing and access control

Integrations ecosystem: LiteLLM integrates natively with a broad observability and infrastructure ecosystem. Supported logging/tracing destinations include Langfuse, Arize Phoenix, LangSmith, MLflow, Helicone, Lunary, OpenTelemetry, Amazon S3, and Google Cloud Storage. Monitoring is supported via Prometheus metrics. Deployment options include Docker, Helm (OCI/GHCR), Kubernetes, Terraform, Render, and Railway. Authentication integrations cover SSO/SAML, JWT, and API Gateway passthrough (e.g., Gloo). Agent framework support includes LangGraph, Vertex AI Agent Engine, Azure AI Foundry, Bedrock AgentCore, and Pydantic AI via the A2A protocol. MCP (Model Context Protocol) gateway integration supports Cursor IDE and custom MCP servers. Provider coverage spans OpenAI, Anthropic, Azure, AWS Bedrock, Google Vertex AI/Gemini, Cohere, Mistral, Groq, HuggingFace, VLLM, NVIDIA NIM, Ollama, Replicate, Databricks, IBM Watsonx, and 80+ additional providers.
Pricing summary: LiteLLM follows an open-core model. The open-source tier is free (MIT license) and includes 100+ LLM provider integrations, virtual keys, budgets, teams, load balancing, RPM/TPM limits, LLM guardrails, and logging integrations (Langfuse, Arize Phoenix, LangSmith, OpenTelemetry). The Enterprise tier (cloud or self-hosted) is priced on a custom, contact-for-pricing basis and adds SSO/SAML, JWT Auth, audit logs, enterprise support with custom SLAs, and a 30-day trial. No public per-seat or usage-based pricing is disclosed.
Review summary: LiteLLM has no verified reviews on G2 (unclaimed profile as of research date). On Product Hunt, reviewer sentiment is strongly positive, with practitioners from companies including Budibase, JDoodle.ai, Crossnode, and Athina AI praising its multi-provider abstraction, OpenAI-compatible proxy, caching, load balancing, and seamless pairing with observability tools like Langfuse. Critical feedback in technical community discussions (Hacker News, Medium, TrueFoundry blog) centers on the operational complexity of running the proxy in production (Redis + PostgreSQL dependencies), enterprise feature paywalling (SSO/RBAC), and limited support for highly custom routing logic.
Competitive positioning: LiteLLM positions itself as the de facto open-source AI Gateway and Python SDK for unified multi-LLM access management. Its primary differentiation is an OpenAI-format-compatible proxy layer that abstracts 100+ LLM providers behind a single, standardized interface, contrasting with pure observability tools (Arize, Langfuse) or evaluation platforms (Galileo, Confident AI). Against managed gateway competitors like Portkey and Helicone, LiteLLM competes on open-source auditability, self-hosted deployment, and breadth of provider coverage (100+ LLMs). With 45K+ GitHub stars and 240M+ Docker pulls, it occupies a high-volume developer mindshare position, while its enterprise tier targets platform teams needing SSO, audit logs, and custom SLAs at scale.
Limitations: Production deployment of the LiteLLM proxy server requires managing external dependencies (Redis for caching/rate limiting, PostgreSQL for spend logs and API keys), adding infrastructure operational burden. Enterprise features including SSO/SAML, RBAC, audit logs, and JWT auth are locked behind a paid Enterprise license, making governance at scale costly. Advanced model routing logic (e.g., prompt-content-conditional routing, highly custom post-processing) is limited compared to custom-built orchestrators. SQLite and broader database backends are not supported by the proxy (by stated design). In early 2025, LiteLLM experienced a supply chain security incident in which compromised versions (1.82.7–1.82.8) were published to PyPI via a hijacked Trivy CI dependency; the affected packages were removed within approximately three hours and the team issued a public security townhall.


### Source urls

- https://litellm.ai/
- https://github.com/berriai/litellm
- https://docs.litellm.ai/docs
- https://www.ycombinator.com/companies/litellm
- https://www.producthunt.com/products/litellm/reviews
- https://www.truefoundry.com/blog/a-detailed-litellm-review-features-pricing-pros-and-cons-2026
- https://www.trendmicro.com/en_us/research/26/c/inside-litellm-supply-chain-compromise.html
- https://pitchbook.com/profiles/company/520687-72
- https://grokipedia.com/page/LiteLLM

Reviewed at: 2026-05-06T17:53:55.636+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| Netflix | Netflix's GenAI platform team uses LiteLLM to provide developers with Day-0 access to new LLM models within a day of release, eliminating the need to transform inputs and outputs across providers. | Saved months of engineering work on provider integration |
| Lemonade | Lemonade's GenAI platform uses LiteLLM alongside Langfuse to streamline the complexity of managing multiple LLM models across their platform. | Not available |



### Reviews breakdown





### Review themes



#### Praised

- Unified API across 100+ LLM providers with no SDK juggling
- Drop-in OpenAI compatibility — swap providers without rewriting code
- Easy load balancing and fallback configuration
- Cost tracking and spend management per team/user/org
- Open-source and self-hostable for compliance and control
- Pairs well with observability tools like Langfuse
- Fast release cadence and large contributor community
- Minimal latency overhead vs. direct provider calls



#### Criticized

- Production proxy requires managing Redis and PostgreSQL infrastructure
- SSO, RBAC, and audit logs paywalled behind Enterprise license
- Advanced/conditional routing logic is limited
- 2025 supply chain security incident (quickly remediated)
- Documentation can lag behind rapid release cadence
- Not suitable for complex agent orchestration without pairing with LangChain/LlamaIndex
- Open-source code quality concerns raised in community discussions




### Company facts

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


#### Founders

- Krrish Dholakia
- Ishaan Jaffer

Employees range: 11-50
Total funding: $2.1M
Valuation: Not available
Arr: ~$2.5M
Customer count: Not available
Status: Private


Readiness: Not available


## Ranking

| Display name | Pair count | Total pairs | Presence percent | Avg position |
| --- | --- | --- | --- | --- |
| Arize AI | 45 | 125 | 36 | 3.0757575757575757 |
| Langfuse | 31 | 125 | 24.8 | 2.3260869565217392 |
| LangChain | 26 | 125 | 20.8 | 3.4651162790697674 |
| Braintrust | 22 | 125 | 17.599999999999998 | 3.176470588235294 |
| LiteLLM | 11 | 125 | 8.799999999999999 | 2.9 |
| Portkey | 10 | 125 | 8 | 2.9285714285714284 |
| Confident AI | 10 | 125 | 8 | 4.764705882352941 |
| Galileo | 4 | 125 | 3.2 | 5.833333333333333 |
| Helicone | 3 | 125 | 2.4 | 2 |
| Traceloop | 2 | 125 | 1.6 | 3.6666666666666665 |
| Patronus AI | 1 | 125 | 0.8 | 1 |



## Platform breakdown

| Platform | Prompt count | Presence rate |
| --- | --- | --- |
| perplexity | 4 | 16 |
| google-ai-mode | 3 | 12 |
| bing-copilot-search | 0 | 0 |
| chatgpt-search | 2 | 8 |
| google-ai | 2 | 8 |



## Strengths

| Prompt text | Platform count | Avg position |
| --- | --- | --- |
| Which LLM observability tools work with OpenTelemetry-compatible backends so we can consolidate LLM traces alongside existing service traces? | 1 | 1 |
| What platforms support end-to-end tracing of multi-agent pipelines including tool calls, retrieval steps, and sub-agent spawning? | 1 | 1 |
| I'm evaluating LLM gateway solutions for a startup — which ones have the simplest self-hosted setup with a working UI on day one? | 2 | 1 |
| Which LLM gateways add the least latency overhead when routing between LLM providers — safe to use in production for sub-500ms SLAs? | 2 | 1.5 |



## Gaps

| Prompt text | Competitor presence count |
| --- | --- |
| 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. | 5 |
| Which LLM observability platforms integrate natively with the most popular agent frameworks so traces appear automatically with no manual instrumentation? | 5 |
| Which evaluation platforms for LLM outputs are easiest to plug into an existing CI pipeline for a five-engineer team? | 5 |
| What LLM tracing platforms handle high-throughput production workloads — millions of traces per day — without degrading query performance? | 4 |
| Which LLM evaluation platforms support custom rubric-based scoring for domain-specific correctness beyond generic faithfulness metrics? | 4 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 2 |
| Developer Experience | 5 | 0 |
| Integrations & Ecosystem | 5 | 2 |
| Performance & Reliability | 5 | 2 |
| Setup & First Run | 5 | 1 |



## 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search

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



##### Chatgpt-search

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



##### Google-ai

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


- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai

| Display name | Position |
| --- | --- |
| Portkey | 5 |


- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Braintrust | 1 |
| Confident AI | 4 |
| Arize AI | 5 |



##### Chatgpt-search

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



##### Google-ai

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


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


#### Brand position by platform

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Braintrust | 2 |



##### Bing-copilot-search

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



##### Chatgpt-search

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



##### Google-ai

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


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


#### Brand position by platform

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai




- 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

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: 3
Google-ai: Not available



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Langfuse | 2 |
| Helicone | 3 |



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity





##### Google-ai-mode

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



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Confident AI | 6 |



##### Chatgpt-search

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



##### Google-ai

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


- 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

Perplexity: 1
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: 2



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Helicone | 2 |



##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai

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


- 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

Perplexity: 4
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: 1
Google-ai: Not available



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




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


#### Brand position by platform

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search

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



##### Chatgpt-search

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



##### Google-ai

| Display name | Position |
| --- | --- |
| Confident AI | 2 |


- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search

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



##### Chatgpt-search

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



##### Google-ai

| Display name | Position |
| --- | --- |
| LangChain | 3 |


- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Portkey | 3 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Braintrust | 5 |



##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Galileo | 4 |



##### Chatgpt-search

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



##### Google-ai

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


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


#### Brand position by platform

Perplexity: 2
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: 4



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai

| Display name | Position |
| --- | --- |
| Portkey | 1 |
| LiteLLM | 4 |
| LangChain | 5 |


- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode





##### Bing-copilot-search

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



##### Chatgpt-search

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



##### Google-ai




- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search





##### Chatgpt-search

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



##### Google-ai

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


- 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

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



#### Platform rows



##### Perplexity

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



##### Google-ai-mode

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



##### Bing-copilot-search

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



##### Chatgpt-search

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



##### Google-ai

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





## Top sources

| Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count |
| --- | --- | --- | --- | --- | --- | --- | --- |
| https://www.litellm.ai/enterprise | Enterprise | litellm.ai | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/b47f69ae-9962-4274-829c-bf8a1c5e86b4/46f37f26eb06947c10aeecce590829d79619b7ac.png | commercial | landing_page | 8 | 8 |
| https://docs.litellm.ai/docs/benchmarks | Benchmarks \| liteLLM | docs.litellm.ai | Not available | commercial | documentation | 7 | 7 |
| https://docs.litellm.ai/docs/enterprise | Security And Access​ | docs.litellm.ai | Not available | commercial | documentation | 6 | 6 |
| https://docs.litellm.ai/docs/observability/opentelemetry_integration | OpenTelemetry v1 | docs.litellm.ai | Not available | commercial | documentation | 4 | 4 |
| https://docs.litellm.ai/docs/proxy/docker_quick_start | Quickstart | docs.litellm.ai | Not available | commercial | documentation | 3 | 3 |
| https://www.litellm.ai/ai-gateway | AI Gateway for Agents, MCPs & LLM Routing - LiteLLM | litellm.ai | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/b47f69ae-9962-4274-829c-bf8a1c5e86b4/46f37f26eb06947c10aeecce590829d79619b7ac.png | commercial | product_page | 3 | 3 |
| https://docs.litellm.ai/docs/ | Getting Started - LiteLLM Docs | docs.litellm.ai | Not available | commercial | documentation | 2 | 2 |
| https://docs.litellm.ai/docs/proxy/security_best_practices | Security Best Practices | docs.litellm.ai | Not available | commercial | documentation | 2 | 2 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| Which LLM observability tools work with OpenTelemetry-compatible backends so we can consolidate LLM traces alongside existing service traces? | bing-copilot-search | ...oss gateway + observability + guardrails \| Yes \| Apache-2.0 core \| Combines routing, observability, and safety in one \| \| LiteLLM \| OTel-native gateway \| Yes \| OSS \| Lightweight routing plus observability hooks \| \| OpenLIT / OpenLLMetry / OpenInfer... |
| I'm evaluating LLM gateway solutions for a startup — which ones have the simplest self-hosted setup with a working UI on day one? | bing-copilot-search | The simplest self‑hosted LLM gateways with a working UI on day one are: (1) d‑rohan’s LLM Gateway, (2) sxueck’s LLM Gateway, and (3) LiteLLM + Open WebUI. |
| Which LLM gateways add the least latency overhead when routing between LLM providers — safe to use in production for sub-500ms SLAs? | bing-copilot-search | LLM Gateways in Production: Comparing LiteLLM, Portkey, Kong AI Gateway, and Cloudflare AI Gateway Architecture, Fallback Cascades, and Serving Economics — LLMs Blog ⚡ Gateway Latency Comparison (2025–2026) ---------------------------------------- \| G... |



## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| perplexity | Langfuse | Langfuse looks like a strong fit for the workflow you described. Its UI lets teammates comment directly on traces, individual observations, sessions, and prompts, with threaded discussion, @mentions, and emoji reactions—so PMs can flag quality issues... |
| google-ai-mode | LangChain | Docs by LangChain +1 * * * * The Experience: Widely considered the gold standard for production-grade LLM evaluation. |
| google-ai-mode | Langfuse | The Experience: Langfuse provides an open-source/cloud prompt management system paired with an interactive prompt playground. |
| bing-copilot-search | Confident AI | For collaborative LLM observability where engineers and PMs can review trace quality without SQL, the strongest options are Confident AI, Braintrust, and LangSmith. |
| chatgpt-search | Langfuse | Langfuse is the closest fit for your specific requirement. Its UI is explicitly designed for product teams: PMs can replay conversations, use annotation queues, score traces, leave comments/@mentions, and ask questions in plain language—without SQL. |
| google-ai | Confident AI | Confident AI * Collaboration highlights: Built-in evaluation workflows and human labeling features allow product and quality teams to review flagged traces and build golden datasets without writing queries. |
| perplexity | Langfuse | Langfuse and Arize Phoenix are strong fits for broad, framework-native tracing; LangSmith is especially seamless for LangChain/LangGraph, but its support for other frameworks may take additional setup. - Langfuse lists integrations for LangChain... |
| google-ai-mode | Langfuse | ...typically requires platforms that treat prompts and test configs as code or provide deep CI/CD workflow integrations . Langfuse +1 The leading evaluation and prompt-management platforms that handle this linkage vary by how tightly they integrate in... |
| bing-copilot-search | Arize AI | LLM Observability Tools Compared (2026)Arize AI. 14 Best AI Observability Tools for Agents in 2026 \| Arizelaminar.sh. |
| chatgpt-search | Langfuse | Langfuse — broadest native framework coverage: LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, Google ADK, Pydantic AI, Claude Agent SDK, etc. \[1\] * LangSmith — deepest automatic integration with LangChain/LangGraph, but less framework-agnostic. |
| google-ai | LangChain | When looking for LLM observability platforms that integrate natively with popular agent frameworks (like LangChain, LlamaIndex, CrewAI, AutoGen, and Pydantic AI) to provide automatic, zero-manual-instrumentation tracing, a few leading platforms stand out. |
| perplexity | Braintrust | For a five-engineer team, I’d shortlist Promptfoo and Braintrust first. Both have straightforward CI paths; the better fit depends on whether you want a lightweight test runner or a hosted evaluation workflow. |



## Trend

Visibility delta: 4
Avg position delta: -0.20000000000000018
Citation count delta: -15