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DeepInfra.com is a serverless AI inference platform giving developers access to 100+ open-source and commercial models — including Llama, DeepSeek, Mistral, and Qwen — through a simple, OpenAI-compatible API.
AUQ was brought in to solve two interconnected challenges: building a technical SEO infrastructure fast enough to capture demand around new model releases, and creating a repeatable content and go-to-market engine to support them.
When a new LLM drops, developer search demand spikes within hours. Being indexed first means capturing that wave before competitors. DeepInfra’s infrastructure couldn’t support that speed, and their content operation wasn’t built to move at the pace of the model release cycle. The subject matter is also deeply technical — writing accurately about inference endpoints and GPU performance requires authors who actually understand the space.Friction Points
AUQ ran a deep technical audit and rebuilt DeepInfra’s crawl infrastructure around speed — crawl budget optimization, internal linking, sitemap improvements, and structural changes so new model pages are discoverable the moment they’re published.
For each new model release, AUQ executes a repeatable launch playbook: pre-launch keyword research, automated content production, a timed linkbuilding sprint, and internal linking from existing high-traffic pages to new content.
Content runs in two tracks. For developers: expert authors with real ML infrastructure experience write thought leadership on inference optimization, GPU pricing, and model benchmarking. For scale: automated production covers model and feature pages.
For LLM discoverability, AUQ builds niche listicles, definitional pages, and long-tail landing pages targeting specific model names and use cases — the formats AI assistants prefer to cite. AUQ stays current on what’s actually validated about how LLMs crawl content and updates formats accordingly. AUQ’s design team also built DeepInfra’s landing and model family pages with developer UX and conversion in mind.
Rather than optimizing purely for anchor text, AUQ prioritizes getting DeepInfra featured in inference provider comparisons, model roundups, and developer tool articles — the content AI assistants draw from when recommending platforms. Reddit and developer communities are key channels for brand mentions that shape LLM recommendations.
AUQ’s GTM and GA4 setup ties traffic to signups and API activations in a Looker Studio dashboard. Prompt tracking monitors DeepInfra’s presence in AI-generated inference queries.
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