Leaderboard · updated 18 September 2026
AI Observability Leaderboard
18 observability products ranked on 10 documented criteria, on one table the reader re-weights for the question they are asking. The top score is 100 of 100, as of September 2026. Of the 210 judged cells, 113 are documented outright, 81 exist with a gating condition and 16 are a documented absence. Every one links the page it was checked against, and all 202 of those links were fetched on 18 September 2026. A mark is what a vendor documents, checked page by page, rather than what a product was measured doing here. Overhead and ingest cost have no column. Last change 18 September 2026.
LLM and agent observability, ranked on what the documentation shows. One table, not one per category: the controls above it choose the view, narrow to platforms or to tools, and re-weight the whole ranking for the question you are actually asking.
We went through every product on this table, criterion by criterion, in its own documentation on 18 September 2026, and recorded what we found in each of the 202 pages we cite. All of those links were fetched again against the live site on 18 September 2026. None was broken.
How we checked
- Every mark was checked against the vendor's own page
- We worked through the ten criteria for each product in turn, in its own documentation, API reference and repository, and linked the page each answer came from. A tick says the mechanism is documented at the strictness the criterion asks for. It does not say it was installed and exercised here, and a well-documented tracer can still be a slow one.
- Then we tried to knock our own findings down
- An adversarial pass went back over every tick, every documentation-root link and every marketing source, instructed to refute where it was uncertain, and it moved 19 cells. The 81 partial cells were not put through it, so a partial has been examined less closely than a tick.
- Overhead and ingest cost have no column
- Instrumenting an application costs latency and the backend costs money to run. No independent, machine-readable benchmark exists for either across these products, so there is nothing every product could be measured against the same way, and building a column out of vendor claims would be worse than leaving it out.
- Two columns are not yet fit to rank on
- CI/CD gating discriminates badly, and compliance is sourced more thinly than anything else here. Both are written up under Cautions, with what would fix them. Read the other eight with more confidence than those two.
- Some cells rest on an index rather than a page
- 5 judged cells link a documentation root or a machine-readable link dump rather than a page about the criterion. An index is weak evidence that a feature exists and no evidence at all that it does not. Those cells are marked on the page, and replacing them is the first job of the next pass.
- What the board covers so far
- We have read the documentation of 22 products, and 18 of them carry enough to rank. A product that is not here has not been weighed and found wanting; its documentation is the next thing we read.
Documented capability, across ten criteria
22 products · 210 judged cells · last verified 18 September 2026
A tick is a page in the vendor’s own documentation showing the feature at the strictness the criterion asks for. A half is a feature that exists with a gating condition or at reduced scope. A cross is a documented absence. A dash means the criterion does not apply to this kind of product, and it leaves both sides of the ratio rather than counting as a zero. Open any cell to see the page it was checked against.
Matrix
Every criterion of every product, with the page each status was checked against.
Every criterion counts the same. The default, and the only one that makes no assumption about what you are building.
| Tracing | Evaluation | Cost | Security | Developer experience | Portability | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Rank | Product | Score | Evidence | OTel | Agents | Online evals | CI gating | Cost | PII | Self-host | SOC2/HIPAA | Prompts | Egress |
| 1 | LangfuseLangfuse / ClickHouse●★ 34,729 | 100 of 100 | 100%documentation | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| 2 | BraintrustBraintrust Data | 90 of 100 | 100%documentation | ✓ | ✓ | ✓ | ◑ | ✓ | ✓ | ◑ | ✓ | ✓ | ✓ |
| 3 | DeepEvalConfident AI★ 18,313 | 90 of 100 | 100%documentation | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ◑ | ◑ | ✓ | ✓ |
| 4 | LangSmithLangChain | 90 of 100 | 93%1 on marketing | ✓ | ✓ | ✓ | ◑ | ✓ | ✓ | ◑ | ✓ | ✓ | ✓ |
| 5 | W&B WeaveWeights & Biases (CoreWeave)●★ 1,129 | 85 of 100 | 100%documentation | ✓ | ✓ | ✓ | ◑ | ◑ | ✓ | ◑ | ✓ | ✓ | ✓ |
| 6 | Datadog LLM ObservabilityDatadog● | 85 of 100 | 93%1 on marketing | ✓ | ✓ | ✓ | ◑ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ |
| 7 | Comet OpikComet★ 22,099 | 85 of 100 | 90%1 on marketing | ✓ | ✓ | ✓ | ◑ | ◑ | ✓ | ✓ | ◑ | ✓ | ✓ |
| 8 | LiteLLM ProxyBerriAI★ 59,007 | 80 of 100 | 100%documentation | ✓ | ◑ | ✓ | ✗ | ✓ | ✓ | ✓ | ◑ | ✓ | ✓ |
| 9 | Pydantic LogfirePydantic★ 4,478 | 80 of 100 | 100%documentation | ✓ | ✓ | ✓ | ◑ | ◑ | ✓ | ◑ | ✓ | ◑ | ✓ |
| 10 | Fiddler AIFiddler | 75 of 100 | 93%1 on marketing | ✓ | ✓ | ✓ | ◑ | ◑ | ◑ | ✓ | ✓ | ✗ | ✓ |
| 11 | LaminarLaminar (lmnr.ai)●★ 3,265 | 75 of 100 | 93%1 on marketing | ✓ | ✓ | ✓ | ◑ | ✓ | ◑ | ◑ | ◑ | ◑ | ✓ |
| 12 | Arize PhoenixArize AI★ 11,519 | 72 of 100 | 100%documentation | ◑ | ✓ | ◑ | ◑ | ◑ | ◑ | ✓ | – | ✓ | ✓ |
| 13 | GalileoGalileo● | 70 of 100 | 93%1 on marketing | ✓ | ✓ | ✓ | ◑ | ◑ | ◑ | ◑ | ◑ | ◑ | ✓ |
| 14 | HoneycombHoneycomb | 70 of 100 | 91%1 on a root | ✓ | ✓ | ✗ | ◑ | ✓ | ✓ | ◑ | ✓ | ✗ | ✓ |
| 15 | HeliconeHelicone●★ 6,161last push 16 September 2026 | 65 of 100 | 100%documentation | ◑ | ◑ | ◑ | ✗ | ✓ | ◑ | ✓ | ◑ | ✓ | ✓ |
| 16 | OpenObserveOpenObserve Inc★ 21,993 | 65 of 100 | 93%1 on marketing | ✓ | ◑ | ◑ | ◑ | ◑ | ◑ | ✓ | ◑ | ◑ | ✓ |
| 17 | PortkeyPortkey AI●★ 13,023 | 65 of 100 | 91%1 on a root | ✓ | ◑ | ◑ | ✗ | ✓ | ◑ | ◑ | ✓ | ✓ | ◑ |
| 18 | New Relic AI MonitoringNew Relic● | 45 of 100 | 91%1 on a root | ✓ | ✓ | ✗ | ✗ | ◑ | ◑ | ✗ | ◑ | ✗ | ✓ |
✓ documented, on a page about the criterion · ✓ documented, on a root or a marketing page · ◑ partial · ✗ documented absence · – not applicable · ▼ moved down by the adversarial pass · ▲ put back by the review pass
210 judged cells over 202 distinct source URLs. 0 were broken when every one was fetched on 18 September 2026. 10 rest on vendor marketing and 5 on a documentation root; both are the weakest evidence here and both are marked.
Carried, not ranked
4 of the 22 products audited are not in the ranking. Each one was read against the same ten criteria and each carries the same links; what it does not carry is a rank, because ranking it would compare things that are not alternatives to each other.
whylogs / LangKit
would score 58WhyLabs (acquired by Apple, Jan 2025)★ 2,833
WhyLabs states on its own home page that it is discontinuing operations. The whylogs repository was last pushed on 10 January 2025, twenty months before this audit. Four criteria do not apply to a profiling library at all. The board's earlier label crediting the shutdown to an Apple acquisition had no first-party source behind it and has been dropped rather than corrected.
OpenInference
would score 50Arize AI★ 1,224
A semantic-convention specification and a set of instrumentation libraries, not a product anyone deploys or buys. Five of its ten criteria do not apply, and its own README describes it as complementary to OpenTelemetry rather than an implementation of the GenAI conventions. Ranking it against a platform would compare a standard to the things that implement it.
Evidently
would score 50Evidently AI★ 7,923
Evidently Cloud is no longer sold. Two vendor pages say so, which makes every criterion that assumes a hosted tier moot, and compliance is unsupported for that reason rather than as a finding about the product. The open-source library is active, released 11 September 2026, and is worth using; it is not a hosted platform and is not ranked as one.
AgentOps
would score 45AgentOps AI★ 5,824
No commit since 25 June 2026 and no tagged release since 29 August 2025, twelve months before this audit. Three of its cells rest on an llms.txt link dump or a bare repository landing page, which is not evidence of a feature and is no evidence at all of one's absence. It is carried so the gap is visible, and it is not ranked on evidence this thin.
Ranking
The same figures as a bar, beside how well each row is sourced.
| Rank | Product | Score | Cells | Evidence |
|---|---|---|---|---|
| 1 | LangfuseLangfuse / ClickHouse · platforms | 100 of 10020 of 20 weighted points over 10 criteria | 10 native · 0 partial · 0 absent | 100%documentation |
| 2 | BraintrustBraintrust Data · platforms | 90 of 10018 of 20 weighted points over 10 criteria | 8 native · 2 partial · 0 absent2 moved by review | 100%documentation |
| 3 | DeepEvalConfident AI · tools and libraries | 90 of 10018 of 20 weighted points over 10 criteria | 8 native · 2 partial · 0 absent | 100%documentation |
| 4 | LangSmithLangChain · platforms | 90 of 10018 of 20 weighted points over 10 criteria | 8 native · 2 partial · 0 absent1 moved by review | 93%1 on marketing |
| 5 | W&B WeaveWeights & Biases (CoreWeave) · platforms | 85 of 10017 of 20 weighted points over 10 criteria | 7 native · 3 partial · 0 absent | 100%documentation |
| 6 | Datadog LLM ObservabilityDatadog · platforms | 85 of 10017 of 20 weighted points over 10 criteria | 8 native · 1 partial · 1 absent | 93%1 on marketing |
| 7 | Comet OpikComet · platforms | 85 of 10017 of 20 weighted points over 10 criteria | 7 native · 3 partial · 0 absent | 90%1 on marketing |
| 8 | LiteLLM ProxyBerriAI · tools and libraries | 80 of 10016 of 20 weighted points over 10 criteria | 7 native · 2 partial · 1 absent | 100%documentation |
| 9 | Pydantic LogfirePydantic · tools and libraries | 80 of 10016 of 20 weighted points over 10 criteria | 6 native · 4 partial · 0 absent1 moved by review | 100%documentation |
| 10 | Fiddler AIFiddler · platforms | 75 of 10015 of 20 weighted points over 10 criteria | 6 native · 3 partial · 1 absent1 moved by review | 93%1 on marketing |
| 11 | LaminarLaminar (lmnr.ai) · tools and libraries | 75 of 10015 of 20 weighted points over 10 criteria | 5 native · 5 partial · 0 absent | 93%1 on marketing |
| 12 | Arize PhoenixArize AI · platforms | 72 of 10013 of 18 weighted points over 9 criteria | 4 native · 5 partial · 0 absent · 1 n/a2 moved by review | 100%documentation |
| 13 | GalileoGalileo · platforms | 70 of 10014 of 20 weighted points over 10 criteria | 4 native · 6 partial · 0 absent1 moved by review | 93%1 on marketing |
| 14 | HoneycombHoneycomb · platforms | 70 of 10014 of 20 weighted points over 10 criteria | 6 native · 2 partial · 2 absent1 moved by review | 91%1 on a root |
| 15 | HeliconeHelicone · tools and libraries | 65 of 10013 of 20 weighted points over 10 criteria | 4 native · 5 partial · 1 absent | 100%documentation |
| 16 | OpenObserveOpenObserve Inc · platforms | 65 of 10013 of 20 weighted points over 10 criteria | 3 native · 7 partial · 0 absent1 moved by review | 93%1 on marketing |
| 17 | PortkeyPortkey AI · platforms | 65 of 10013 of 20 weighted points over 10 criteria | 4 native · 5 partial · 1 absent2 moved by review | 91%1 on a root |
| 18 | New Relic AI MonitoringNew Relic · platforms | 45 of 1009 of 20 weighted points over 10 criteria | 3 native · 3 partial · 4 absent1 moved by review | 91%1 on a root |
Carried, not ranked
4 of the 22 products audited are not in the ranking. Each one was read against the same ten criteria and each carries the same links; what it does not carry is a rank, because ranking it would compare things that are not alternatives to each other.
whylogs / LangKit
would score 58WhyLabs (acquired by Apple, Jan 2025)★ 2,833
WhyLabs states on its own home page that it is discontinuing operations. The whylogs repository was last pushed on 10 January 2025, twenty months before this audit. Four criteria do not apply to a profiling library at all. The board's earlier label crediting the shutdown to an Apple acquisition had no first-party source behind it and has been dropped rather than corrected.
OpenInference
would score 50Arize AI★ 1,224
A semantic-convention specification and a set of instrumentation libraries, not a product anyone deploys or buys. Five of its ten criteria do not apply, and its own README describes it as complementary to OpenTelemetry rather than an implementation of the GenAI conventions. Ranking it against a platform would compare a standard to the things that implement it.
Evidently
would score 50Evidently AI★ 7,923
Evidently Cloud is no longer sold. Two vendor pages say so, which makes every criterion that assumes a hosted tier moot, and compliance is unsupported for that reason rather than as a finding about the product. The open-source library is active, released 11 September 2026, and is worth using; it is not a hosted platform and is not ranked as one.
AgentOps
would score 45AgentOps AI★ 5,824
No commit since 25 June 2026 and no tagged release since 29 August 2025, twelve months before this audit. Three of its cells rest on an llms.txt link dump or a bare repository landing page, which is not evidence of a feature and is no evidence at all of one's absence. It is carried so the gap is visible, and it is not ranked on evidence this thin.
Evidence
Which rows rest on documentation, which on a repository, and which on marketing.
| Product | Official documentation | Source repository | Vendor marketing | On a root | Moved by review |
|---|---|---|---|---|---|
| Langfuseplatforms | 10 | — | — | — | — |
| Braintrustplatforms | 10 | — | — | — | 2 |
| DeepEvaltools and libraries | 10 | — | — | — | — |
| LangSmithplatforms | 9 | — | 1 | — | 1 |
| W&B Weaveplatforms | 10 | — | — | — | — |
| Datadog LLM Observabilityplatforms | 9 | — | 1 | — | — |
| Comet Opikplatforms | 8 | 1 | 1 | — | — |
| LiteLLM Proxytools and libraries | 10 | — | — | — | — |
| Pydantic Logfiretools and libraries | 10 | — | — | — | 1 |
| Fiddler AIplatforms | 9 | — | 1 | — | 1 |
| Laminartools and libraries | 9 | — | 1 | — | — |
| Arize Phoenixplatforms | 9 | — | — | — | 2 |
| Galileoplatforms | 9 | — | 1 | — | 1 |
| Honeycombplatforms | 10 | — | — | 1 | 1 |
| Heliconetools and libraries | 10 | — | — | — | — |
| OpenObserveplatforms | 9 | — | 1 | — | 1 |
| Portkeyplatforms | 10 | — | — | 1 | 2 |
| New Relic AI Monitoringplatforms | 10 | — | — | 1 | 1 |
| whylogs / LangKitcarried, not ranked | 6 | — | — | — | 2 |
| OpenInferencecarried, not ranked | — | 5 | — | — | 2 |
| Evidentlycarried, not ranked | 9 | 1 | — | — | 1 |
| AgentOpscarried, not ranked | 6 | 1 | 3 | 2 | 1 |
Cautions
What this board knows about its own weak spots, including two columns not yet fit to rank on.
The CI gating column does not yet discriminate
CI gatingThree of twenty-two products clear the bar as written, against eleven partials. Worse, the first pass scored an identical pytest plugin as native for one product and partial for four others, which means the column was measuring the auditor as much as the product. The rule now states explicitly that a test-runner assertion counts only where the vendor documents comparing against a threshold or a baseline. Read this column as a rough signal until the next pass re-checks every cell under that line.
The compliance column is the weakest sourced on the board
SOC2/HIPAACertification evidence usually lives off the vendor's own domain, behind a trust portal. Ten cells on this board rest on vendor marketing and most of them are this column; one product's report chain terminates on a third-party compliance portal, which the board's own sourcing rule does not accept. A trust centre that names the report and how to obtain it is scored native, a checkmark in a pricing table is not, and two products sit on exactly that checkmark.
Only the native claims were attacked
An adversarial pass challenged every native cell, every documentation-root fallback and every vendor-marketing source, and moved fifteen of them. It did not challenge the eighty-two partial cells, which is where the soft judgement calls sit. A review pass then checked the attacks themselves and put four cells back that had been wrongly refuted. Until the partials get the same treatment, treat a partial as less examined than a native.
Ownership moves faster than documentation
Six of these twenty-two products changed hands or changed shape within the audit window, and not one of the vendors' documentation sites says so. Langfuse is owned by ClickHouse, Galileo by Cisco, Weights & Biases by CoreWeave, and New Relic has been private since 2023. Datadog renamed the product to Agent Observability while leaving the documentation path unchanged. These were found by reading company pages and repository activity, not capability documentation, which is why this board records a repository fact beside every open-source row.
Absence is harder to prove than presence
Five cells assert that a product does not have a feature by linking a documentation root or a machine-readable link dump. An index is not evidence of absence, and the target changes under the citation without notice. Those cells are marked on the page as resting on a root, and they are the first thing the next pass should replace with a page a reader can inspect.
Where the market thins out
How the 18 ranked products fare on each criterion, fewest documented first. A criterion only one product documents is telling you about the market rather than about that product.
| Criterion | Native | Partial | Absent | N/A |
|---|---|---|---|---|
| CI/CD PR gatingEvaluation · partial when: Evals run in CI but nothing fails the build on a regression threshold. A test-runner assertion counts as a gate ONLY where the vendor documents comparing against a threshold or a baseline; a plugin that merely lets you write your own assert does not, because otherwise every testing library on the board is native. | 2 | 12 | 4 | — |
| Self-hostingSecurity · partial when: An enterprise plan or licence key gates it, the vendor keeps the control plane in a hybrid split, or only a local single-process dev mode is documented. | 7 | 9 | 2 | — |
| SOC 2 Type II and HIPAASecurity · partial when: Only one of the two is evidenced, or the claim is a sentence on a product or pricing page with no report and no trust centre behind it. A trust centre that names the report and how to obtain it is native; a checkmark in a pricing table is not. | 9 | 8 | 0 | 1 |
| Granular cost attributionCost · partial when: Spend is totalled or rolled up by trace, span, model or project, but cannot be split by at least one of user, key, environment or prompt version. | 10 | 8 | 0 | — |
| Client-side or edge PII redactionSecurity · partial when: Scrubbing happens server-side after ingestion, or capture is merely off by default. A gateway or proxy you run inside your own VPC counts as native; a gateway the vendor hosts does not. | 10 | 8 | 0 | — |
| Prompt registryDeveloper experience · partial when: Prompts are stored and versioned but nothing documents deploying a version or rolling one back. A playground with no versioning is not this. | 11 | 4 | 3 | — |
| Production online evalsEvaluation · partial when: Only offline dataset evaluation, or live scoring that is informational and cannot be attached to production traces by a rule. | 12 | 4 | 2 | — |
| Multi-agent and tool/MCP tracingTracing · partial when: Steps and tool calls are captured but nothing renders them as a graph or timeline. Flat LLM-call logging alone is not enough. | 14 | 4 | 0 | — |
| OpenTelemetry GenAITracing · partial when: OTLP is accepted but the GenAI conventions are mapped partially, or the only evidence is a single-provider recipe or an SDK page. A proprietary SDK that calls itself tracing is not this, and OpenInference is its own convention rather than the GenAI one. | 16 | 2 | 0 | — |
| Raw data egress and APIPortability · partial when: A CSV or UI download only, an export of derived summaries rather than the traces, or a write-only API with no documented read path. | 17 | 1 | 0 | — |
How the rank is computed
The rule, in full
One table, not one per category. A row is an observability product, and platforms and tools are ranked together because they are bought as alternatives to each other: a team choosing how to see inside its agents weighs a hosted platform against a library it runs itself. The control above the table narrows to platforms and tools and libraries when the comparison is not the one you want, and the ranks renumber over what is left.
The score. Weighted points over the weighted maximum, scaled to 100. A documented feature earns two, a partial one earns one, a documented absence earns nothing. A criterion that does not apply to a kind of product leaves both sides of the ratio, which is what lets an instrumentation library sit on the same table as a platform without being punished for having no prompt registry. There are 10 such cells.
Six weightings, one dataset. Every criterion counts the same. The default, and the only one that makes no assumption about what you are building. The other five weight the same ten cells for autonomous agents, regulated enterprise, high-throughput saas, continuous quality gating, and full-stack apm. Nothing is re-audited when the reader switches; the same statuses are re-weighted, and the arithmetic in the browser is the module the build ranked with, so the two cannot drift.
Evidence is reported beside the score, never inside it. Every applicable cell here carries a status and a link, so coverage separates nothing. What varies is the quality of the sourcing: 10 cells rest on vendor marketing and 5 on a documentation root rather than a page about the criterion. A tick backed by a page about the criterion is copper; one resting on a root or on marketing is grey. Scoring our own sourcing would be marking our own work, so the figure sits next to the score and the reader weighs it.
The claims were attacked before they were published. After the first read, an adversarial pass went after every tick, every root link and every marketing source, instructed to default to refuted where it was uncertain. It moved 19 cells, almost all of them down. A review pass then checked the attacks themselves and put four cells back that had been wrongly refuted. Both kinds of move are marked on the cell and carry their reason, because a board that hides its own disagreements is asking to be trusted rather than read.
Where it is weak, it says so. The partial cells were never attacked, which makes a partial less examined than a tick. Two criteria, CI/CD gating and compliance, are not yet fit to rank on and are written up under Cautions with what would fix them. 5 cells assert something from an index rather than a page. None of that is in a commit message; it is on the page, because it changes how much the order is worth.
Ties. Scores are compared as displayed, because the data underneath is 10 three-state cells a product and a sub-point gap is not real precision. A tie goes to the better-sourced row, then to the one with more documented cells, then to the name.
Two dates, kept apart. The documentation was read on 18 September 2026 from each vendor's own documentation, API references, source repositories and trust pages, and every link and repository fact was re-checked on 18 September 2026. Collapsing them into one would hide the gap that makes the second pass worth running: the draft this board was built from had three dead links and four moved ones a single day after it was generated.
Left out5
- Overhead, latency and ingest throughput. Nothing here is run, so nothing is scored on what it costs to run. A mark says a mechanism is documented and nothing more.
- Pricing. Most of these publish a free tier, a usage tier and an enterprise price that is a conversation, and a column of those would compare three different things.
- Third-party aggregate scores. Six of the ten sources an early draft leaned on were anonymous, or sold a competing product and ranked themselves. None of them decides anything here; every cell is checked against the vendor's own page instead.
- GitHub stars as a score. They are shown for the open-source rows because attention is worth knowing, and they break a tie and do nothing else. The repository dates beside them are the useful part: two products on this board read as current in their documentation and had stopped shipping.
- Any single composite capability figure that is not the sum of its own parts. The draft this board replaced carried a hand-set capability number weighted at 70 percent of the total, and recomputing it from its own nine sub-scores moved the ranking.
Changes
18 September 2026 · First publication6
- The AI Observability Leaderboard is published. Twenty-two products were read against ten documented criteria, 220 cells in all, and every judged cell links the page it was checked against. Eighteen are ranked on one table the reader re-weights for six kinds of reader; four are carried and not ranked, each with its reason on the page.
- All 202 distinct source links were fetched on the day of publication. None was broken. Five New Relic pages rate-limited an automated sweep and were re-checked one at a time in a browser.
- An adversarial pass attacked every documented claim, every documentation-root link and every vendor-marketing source, and moved fifteen cells, almost all of them down. A review pass then checked those attacks and put four cells back that had been wrongly refuted. Both kinds of move are marked on the cell and carry their reason.
- whylogs / LangKit: whylogs and LangKit are carried and not ranked. WhyLabs states on its own home page that it is discontinuing operations, and the repository was last pushed on 10 January 2025. An earlier draft credited the shutdown to an Apple acquisition; no first-party source says so, and the claim has been dropped rather than corrected.
- AgentOps: AgentOps is carried and not ranked: no commit since 25 June 2026 and no tagged release since 29 August 2025. Its documentation reads as current and says none of this.
- Datadog LLM Observability: Datadog has renamed the product from LLM Observability to Agent Observability. The documentation path is unchanged, and the HIPAA-eligible services list carries the new name with the old one in brackets.
Questions
What does a tick mean?
That the vendor's own documentation shows the feature at the strictness the criterion asks for. It does not mean the feature was installed, exercised or found to work. Nothing on this board was run. A half means the feature exists with a gating condition or at reduced scope: an enterprise plan, a hybrid where the vendor keeps the control plane, scrubbing that happens after ingestion rather than before. A cross means a page was checked and the feature is documented as absent.
Why is a not-applicable cell not a zero?
Because it is not a failure. An instrumentation library has no prompt registry and no hosted compliance posture, and scoring those as zero would rank libraries last for being libraries. A not-applicable cell leaves both the numerator and the denominator, which is what lets a tool and a platform share one table. There are 10 of them.
How is the score computed?
Weighted points over the weighted maximum, scaled to 100. A documented feature earns two points, a partial one earns one, a documented absence earns nothing, and a not-applicable criterion is not in the sum at all. The six weightings above the table change which criteria carry more: balanced counts all ten the same, and the other five weight for autonomous agents, regulated enterprise, high-throughput SaaS, continuous quality gating and full-stack APM.
Why is there an evidence figure beside the score?
Because coverage no longer separates anything here. Every applicable cell on this board carries a status and a link, so a row cannot look better by having been checked more. What still varies is how good those links are: 10 cells rest on vendor marketing and 5 on a documentation root rather than a page about the criterion. The evidence figure says so beside the score, and never inside it, because a board that scored its own sourcing would be marking its own work.
Which columns should I not trust yet?
Two. CI/CD PR gating has three products clearing the bar out of 18, and the first pass scored an identical testing plugin as documented for one product and partial for four others, which means it was measuring the auditor as much as the product. SOC 2 Type II and HIPAA is the weakest sourced column on the board: certification evidence usually lives behind a third-party trust portal, off the vendor's own domain, which the sourcing rule does not accept. Both are written up under Cautions.
Why are some products not ranked?
4 of the 22 audited carry a row and no rank, each with its reason on the page: a vendor winding down, a semantic-convention specification that is not a product anyone deploys, a platform whose hosted tier has been withdrawn, and a project with no commit in three months whose cells rest on a link dump. They were read against the same criteria and carry the same links. Ranking them would compare things that are not alternatives to each other.
What were the up and down arrows on some cells?
A cell that moved after the first read. A down arrow means an adversarial pass attacked the claim and the evidence did not hold, so the status here is the lower one; 19 cells carry a mark of either kind. An up arrow means a review pass checked that attack, found it wrong and put the cell back. Only the documented claims were attacked, so a partial cell has been examined less than a tick, which is the opposite of what you might expect.
Do GitHub stars affect the score?
Never. They are shown for the 15 open-source rows because attention is worth knowing, they break a tie, and they do nothing else. The dates beside them are the useful part. Two products on this board read as entirely current in their documentation and had stopped shipping: one had not been pushed to in twenty months, and one commits daily with no tagged release in thirteen. No vendor's own site says so.
Why does the documentation never mention who owns these companies?
Because documentation is written about products, not about ownership. Six of these products changed hands or changed shape inside the audit window and not one documentation site says so: Langfuse is owned by ClickHouse, Galileo by Cisco, Weights & Biases by CoreWeave, and Datadog renamed its product while leaving the URL alone. Those were found by reading company pages and repository activity, which is why every open-source row carries a repository fact beside it.
How often does this update?
There is no fixed schedule. The date at the top is the last time the data changed, not the last time the page was built. A weekly job checks every source link still resolves and opens an issue when one does not; it never edits a status.