Moderation pipelines
Multi-modal policy enforcement with calibrated human review where stakes demand it.
Industry
AI for Media & Entertainment
Scale content operations and personalization while keeping brand safety and rights in check.
- 90%moderation decisions automated safely
- +20%engagement from better recommendations
- 50%faster content production workflows
Capabilities
AI for content at scale
Content moderation, recommendations and ad optimization for media companies.
Recommendations
Personalization that lifts engagement while respecting editorial and brand values.
Ad optimization
Contextual targeting, brand safety and yield intelligence across inventory.
Production copilots
Research, metadata, versioning and localization support for content teams.
How we deliver in media
Scale the catalog, keep the judgment
Media AI has to move at content speed without losing editorial standards. We automate the volume and route the judgment calls.
Trust and safety
Moderation that scales with your community
Multi-modal classification against your policies, confidence-based routing to human reviewers, and full decision trails — coverage without the burnout.
- Text, image, audio and video policy enforcement
- Calibrated thresholds per policy severity
- Reviewer tooling with context and precedents
✓PII detected & redactedenforced
✓Answer grounded in sourcespassed
✓Role-based data accessenforced
✕Out-of-scope tool callblocked
SOC 2GDPRAudit logHITL
Audience
Recommendations tuned to your values
Engagement models balanced with editorial curation, diversity constraints and brand safety — growth metrics without race-to-the-bottom feeds.
- Personalization with editorial constraints built in
- Cold-start handling for new content and users
- Transparent tuning between engagement and values
99.9%Uptime
1.2sp95 latency
$0.021Cost / task
QualityCostLatencyDrift
Production
Content operations at content speed
Metadata generation, rights-aware asset search, versioning and localization drafts — the unglamorous work that gates every release, automated.
- Automatic tagging and metadata enrichment
- Rights and clearance-aware asset workflows
- Localization drafts with human polish loops
Ingest→
Chunk→
Embed→
Index→
Retrieve
PDFConfluenceSharePointSQLTicketsEmail
Grounded answer…with citations [1] [2] and permissions applied
Use cases
Where media companies deploy AI with us
UGC moderation
Community content policy-checked at platform scale.
Content recommendations
Personalized discovery across catalog and editorial.
Metadata and search
Assets tagged, searchable and rights-aware.
Localization pipelines
Subtitles, dubs and versioning accelerated.
Ad brand safety
Contextual placement and suitability at scale.
Newsroom research
Archive search and verification support for journalists.
Delivery
Industry-first delivery
Every engagement is grounded in your domain — regulations, operating models, and the use cases that actually move the needle.
- Domain-ready use cases
- Compliance-aware design
- Ops & CX impact
- Reusable industry playbooks
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1
Map the domain
Identify high-ROI workflows and risk boundaries.
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2
Prioritize use cases
Score impact, feasibility and data readiness.
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3
Pilot with guardrails
Ship a controlled production pilot fast.
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4
Scale across ops
Expand to adjacent processes with shared platforms.
Moderation coverage went from sampling to everything, with humans on the genuinely hard calls. Appeals dropped because decisions got more consistent, not less.
Works with your stack
Works with your media stack
MAM/DAM, streaming infrastructure and ad platforms integrated for real-time content operations.
- AWS Media Services
- Cloudflare
- Mux
- Adobe Experience
- Brightcove
- Google Ad Manager
- Snowflake
- Kafka
- Anthropic Claude
- OpenAI
- Elasticsearch
- Kubernetes
FAQ
Common questions
Can AI match our editorial standards?
It enforces the standards you encode and routes ambiguity to editors. The win is consistency and coverage — humans set the bar, AI applies it at scale.
How do you handle moderation edge cases?
Confidence thresholds route them to trained reviewers with context and precedent attached. Every human decision feeds back into evals, so the boundary keeps improving.
What about rights and licensing in AI workflows?
Rights metadata gates every automated action — assets without clearance can't flow into outputs, and provenance is logged for every generated derivative.
Does AI-generated metadata actually help discovery?
Substantially — consistent, deep tagging improves search, recommendations and ad contextual matching simultaneously. It's often the highest-ROI starting point.
Next step
Run content operations at 2026 speed
Moderation, metadata or recommendations — pick the bottleneck and we'll unblock it.