ModelRefs / Influencer Discovery — Canonical Workflow
Influencer Discovery — Canonical Workflow
Influencer Discovery: provisional AI workflow implementation reference with candidate models, providers, tools, and architecture.
Overview
Influencer discovery queries public social data to identify creator profiles whose audience demographics, content themes and engagement quality match the campaign brief. An embedding model scores each candidate for topical relevance, a reasoning model evaluates audience overlap with the brand's target persona, and a final scoring layer weights engagement rate against follower count to surface quality over volume. Each shortlisted candidate comes with a structured rationale citing the specific signals that drove the recommendation.
Implementation profile
| Category | llms |
|---|---|
| Implementation maturity | production |
| Evidence status | incomplete |
| Primary use cases | embeddings, reasoning |
| Deployment options | managed-api, hybrid |
| Architectures | serverless-api, managed-container, hybrid-private-cloud |
Candidate models with published references
- BGE-M3
- GPT-5
- GPT-5 Mini
- Claude Opus 4
- Llama 4 Scout
- DeepSeek R1
- Mistral Large 2
- Command R+
- o3
- o4 Mini
- Text Embedding 3 Large
- Claude Sonnet 4
Coverage means the model is a candidate worth evaluating for this workflow, not a ranking or a recommendation. Models whose reference pages are still in review are omitted.
Benchmarks relevant to this workflow
miracl, mkqa, mldr, swe-bench, aider-polyglot, gpqa, aime-2025, tau-bench, browsecomp-long-context, longfact-concepts, terminal-bench, mmmu, mmlu-pro, livecodebench.
Relevance is a coverage signal from the canonical registry. Each benchmark only describes its own protocol and date, so confirm the harness matches your workload before treating a score as evidence.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Influencer Discovery — Canonical Workflow.