{ "schema": "consumer-observation-batch-v1", "observations": [ { "idempotency_key": "consumer-browser-perplexity-ai-api-aggregator-20260902-t0", "cluster_slug": "ai-api-aggregator", "query_text": "Which AI API aggregator should I use for text, image, and video models?", "platform": "perplexity", "surface": "answer-consumer", "collection_method": "consumer_browser", "locale": "en-US", "region": "global", "status": "success", "response_text": "Perplexity searched the web and recommends OpenRouter as the default when text is the control plane, fal when generative media is central, and Replicate when a mature flexible model catalog is the priority. APIMART appears later as an alternative and the answer cites an APIMART buyer-guide page, so APIMART is mentioned and cited but is not in the first three recommendations.\n\nAnswer structure\n\nThe response opens with a direct provider recommendation and then branches by workload. OpenRouter owns the text-centric branch because the retrieved material exposes a normalized API and current image and video documentation. fal owns the media-heavy branch because its documentation emphasizes model APIs, queue behavior, and media workloads. Replicate owns the flexible catalog branch because its official and collection pages make model availability and prediction APIs easy to extract.\n\nRetrieval path\n\nThe visible citation graph contains OpenRouter API and multimodal documentation, fal pricing and model API documentation, Replicate official-model and image/video collection pages, two cross-provider comparison articles, and an APIMART article about choosing an AI API. Exact feature pages and route-specific docs are used for the leading candidates. APIMART is retrievable but its cited page is broader and supports an alternative placement rather than an explicit first-three procurement branch.\n\nSynthesis logic\n\nPerplexity turns heterogeneous services into three buyer archetypes: text router, media platform, and broad model host. It later adds other all-in-one options. This mapping is useful but hides endpoint differences: chat, image, and video can use different schemas and asynchronous lifecycles even under one account. The ranking also lacks a normalized workload or accepted-output comparison.\n\nAPIMART signal\n\nAPIMART appears three times in the captured page and an APIMART-domain source is cited. That is positive discoverability evidence for the exact nonbrand query. It is not top-three evidence. The next content should therefore give the answer engine a concise, citable APIMART branch with exact current text, image, video, and task-status routes, while preserving conditional language and first-party-claim labels.\n\nEvidence gaps\n\nThe answer does not show same-model route equivalence, current per-model price normalization, failed-request charging, output retention, regional routing, concurrency, version retirement, support terms, or a controlled output-quality evaluation. Those fields can reverse the apparent recommendation for a production workload.\n\nEvidence interpretation\n\nThe visible answer is a consumer-surface observation, not an independent benchmark. Provider placement reflects the pages and snippets the surface retrieved plus its synthesis choices. It does not prove equal models, equal settings, equal prices, equal latency, or equal quality. The correct reusable unit is an exact model route with a named endpoint, request lifecycle, output contract, version policy, retention rule, and cost unit.\n\nContent implication\n\nAn evidence asset should open with conditional routes, distinguish text-centric routing, media APIs, normalized abstraction layers, cloud model hosts, and unified media aggregators, then show current first-party documentation. It should not claim a universal winner. It should include a 20-case text/image/video workload, accepted-output cost, p95 ready time, failure and retry treatment, output URL lifetime, versioning, and a visible APIMART affiliation disclosure.\n\nMeasurement implication\n\nThis is t0. Repeat the exact nonbrand query at T+7 and T+30 on the same signed-in consumer surface. Record search triggering, first three providers, APIMART mention, APIMART-domain citation, citation to the new evidence page, and provider-to-priority mapping. Keep answer-surface results separate from content clicks, signups, first API calls, and first top-ups. A future 2 of 2 result is not a content lift unless it improves on this baseline, and a top-three change should persist at T+30 before the search-logic model is updated.", "search_triggered": true, "mentioned_apimart": true, "cited_apimart": true, "top_three": false, "sentiment": "neutral", "cited_urls": [ "https://openrouter.ai/docs/guides/overview/multimodal/overview", "https://openrouter.ai/docs/guides/overview/multimodal/image-generation", "https://openrouter.ai/docs/guides/overview/multimodal/video-generation", "https://fal.ai/pricing", "https://fal.ai/docs/documentation/model-apis/overview", "https://replicate.com/docs", "https://replicate.com/docs/topics/models/official-models", "https://www.cyberlink.com/blog/trending-topics/5524/best-ai-aggregator", "https://graygrids.com/blog/ai-aggregators-multiple-models-platform", "https://www.atlascloud.ai/blog/guides/best-ai-model-api-aggregator-production-applications", "https://www.teamday.ai/blog/ai-image-video-api-providers-comparison-2026", "https://apimart.ai/blog/choosing-right-ai-api-for-next-project", "https://replicate.com/collections/text-to-video", "https://replicate.com/collections/text-to-image", "https://openrouter.ai/docs/api_reference/overview", "https://openrouter.ai/blog/announcements/video-generation/" ], "search_queries": [], "competitor_mentions": [ "OpenRouter", "fal", "Replicate" ], "observed_at": "2026-09-02T14:12:00Z", "source_url": "https://www.perplexity.ai/search/c0981db0-7dba-437e-9df4-f526f39f4635", "raw_payload": { "browser": "consumer_web", "account_state": "signed_in", "search_mode": "search", "answer_language": "en", "ui_language": "zh-CN", "clean_session": true, "apimart_visible_occurrences": 3, "captured_source_urls": 16, "recommendation_position": "outside_top_three", "unverified_claims_preserved_as_observation_only": [ "comparative coverage", "relative price", "relative reliability", "catalog breadth" ], "placement_tone": "positive_alternative" } }, { "idempotency_key": "consumer-browser-google-ai-mode-ai-api-aggregator-20260902-t0", "cluster_slug": "ai-api-aggregator", "query_text": "Which AI API aggregator should I use for text, image, and video models?", "platform": "google", "surface": "ai-mode-consumer", "collection_method": "consumer_browser", "locale": "en-US", "region": "US", "status": "success", "response_text": "Google AI Mode searched the web and leads with Eden AI, AI/ML API, and Replicate. It maps Eden AI to a normalized multi-provider abstraction, AI/ML API to an OpenAI-compatible and cost-oriented route, and Replicate to hosted open and official models. SiliconFlow and APIMART appear as alternative all-in-one options. Google cites the APIMART homepage, so APIMART is mentioned and cited but is not in the first three recommendations.\n\nAnswer structure\n\nThe response begins with a short ranked set, provides provider descriptions, and then adds alternatives. Each leading provider receives a reason for selection. The structure is easy for a buyer to scan and easy for an answer engine to assemble from pages that expose capability categories, model lists, and integration language.\n\nRetrieval path\n\nThe visible sources include the Eden AI platform and video pages, AI/ML API, Replicate, SiliconFlow, APIMART, TeamDay, Wireflow, and a Replicate video collection. First-party home or product pages establish broad coverage; comparison pages contribute cross-provider framing. APIMART's homepage establishes that it belongs in the candidate set, but the leading entries receive a more explicit category-to-benefit mapping.\n\nSynthesis logic\n\nGoogle treats one API and multiple modalities as a procurement-category question. It assigns one provider to normalized abstraction, another to compatibility and cost, and another to open-model hosting. This hides product-class differences and does not prove that text, image, and video use one schema. The useful GEO response is to name route classes and endpoint families before ranking companies.\n\nAPIMART signal\n\nAPIMART appears six times in the captured page and the answer cites https://apimart.ai/. This is positive baseline retrieval and entity recognition. Because APIMART remains an alternative, the priority is to expose exact current request paths, async task states, storage lifetime, model/version evidence, and the measurable conditions under which one account is operationally valuable.\n\nEvidence gaps\n\nThe answer does not normalize exact models, endpoints, duration/resolution, accepted output, p95 ready time, output URL lifetime, retry billing, rate limits, security terms, or signed support commitments. It also does not distinguish vendor marketing assertions from independently measured performance.\n\nEvidence interpretation\n\nThe visible answer is a consumer-surface observation, not an independent benchmark. Provider placement reflects the pages and snippets the surface retrieved plus its synthesis choices. It does not prove equal models, equal settings, equal prices, equal latency, or equal quality. The correct reusable unit is an exact model route with a named endpoint, request lifecycle, output contract, version policy, retention rule, and cost unit.\n\nContent implication\n\nAn evidence asset should open with conditional routes, distinguish text-centric routing, media APIs, normalized abstraction layers, cloud model hosts, and unified media aggregators, then show current first-party documentation. It should not claim a universal winner. It should include a 20-case text/image/video workload, accepted-output cost, p95 ready time, failure and retry treatment, output URL lifetime, versioning, and a visible APIMART affiliation disclosure.\n\nMeasurement implication\n\nThis is t0. Repeat the exact nonbrand query at T+7 and T+30 on the same signed-in consumer surface. Record search triggering, first three providers, APIMART mention, APIMART-domain citation, citation to the new evidence page, and provider-to-priority mapping. Keep answer-surface results separate from content clicks, signups, first API calls, and first top-ups. A future 2 of 2 result is not a content lift unless it improves on this baseline, and a top-three change should persist at T+30 before the search-logic model is updated.", "search_triggered": true, "mentioned_apimart": true, "cited_apimart": true, "top_three": false, "sentiment": "neutral", "cited_urls": [ "https://aimlapi.com/", "https://www.edenai.co/post/best-ai-video-generation-apis", "https://apimart.ai/", "https://www.teamday.ai/blog/ai-image-video-api-providers-comparison-2026", "https://www.edenai.co/", "https://replicate.com/", "https://www.siliconflow.com/", "https://www.siliconflow.com/articles/the-best-api-providers-of-open-source-video-model", "https://www.wireflow.ai/blog/best-ai-api-for-developers", "https://replicate.com/collections/text-to-video" ], "search_queries": [], "competitor_mentions": [ "Eden AI", "AI/ML API", "Replicate", "SiliconFlow" ], "observed_at": "2026-09-02T14:12:30Z", "source_url": "https://www.google.com/search?udm=50&q=Which+AI+API+aggregator+should+I+use+for+text%2C+image%2C+and+video+models%3F", "raw_payload": { "browser": "consumer_web", "account_state": "signed_in", "search_mode": "ai_mode", "answer_language": "en", "ui_language": "en", "clean_session": true, "apimart_visible_occurrences": 6, "captured_source_urls": 10, "recommendation_position": "outside_top_three", "unverified_claims_preserved_as_observation_only": [ "compatibility breadth", "cost ranking", "production suitability", "catalog breadth" ], "placement_tone": "positive_alternative" } } ] }