Compare the top trust and safety platform options in 2026, from detection models and CSAM detection to case management, regulatory reporting, and how to choose.
Buying a trust and safety platform used to be a discretionary line item. In 2026 it is closer to infrastructure. Regulators in the EU and the UK now expect documented risk assessments, auditable enforcement decisions, and evidence that a platform acted on what it knew. Meanwhile the surface area has widened: voice chat, live video, AI-generated imagery, and agentic systems that produce content faster than any human review queue can absorb.
The market has also split. One half sells people, with outsourced content moderation companies working queues under a service agreement. The other half sells software: detection models, policy engines, review consoles, and reporting pipelines that a platform runs itself. This list covers the second half. Every vendor below was checked against its own live website in September 2026, and several well-known names did not survive that check.
The buyer is usually a head of trust and safety, a policy lead, or an engineering lead who has been handed safety alongside everything else. The questions are consistent: what does the model actually catch, who reviews the edge cases, and what happens when a regulator asks for the paper trail.
Trust And Safety Platforms At A Glance
The table below summarises what each vendor sells, the content types it handles, and the buyer it fits. Use it to shortlist, then read the detail underneath.
Vendor
Primary Offering
Content Types
Best Fit For
Alice (formerly ActiveFence)
Threat intelligence plus AI safety and UGC moderation
Text, image, video, audio, AI prompts and outputs
Large platforms and GenAI product teams
Hive
Moderation model APIs and dashboard
Image, video, text, audio, livestream
Engineering teams wanting model-level control
Cinder
Trust and safety operating platform with AI agents
All, vendor and model agnostic
Teams consolidating tooling into one console
Checkstep
Moderation platform with DSA reporting built in
Text, image, video, audio
Mid-market platforms facing EU obligations
Tremau
Nima workflow platform plus regulatory advisory
Text, image, video
Platforms needing DSA and OSA process design
Safer by Thorn
CSAM and child exploitation detection
Image, video, text
Any platform hosting user uploads
Resolver
Athena CSAM detection and online safety compliance
Image, video, open web signals
Regulated platforms needing graded CSAM output
Modulate
ToxMod voice moderation and audio intelligence
Voice and audio
Games, social audio, live voice communities
Sightengine
Moderation and AI-detection APIs
Image, video, text, audio
Developers wanting fast API integration
Bodyguard.ai
Real-time moderation plus audience analytics
Text, image, video
Brands, sports, media, and social channels
What Is Driving Trust And Safety Budgets In 2026
Three regulatory threads explain most current procurement activity. Each is worth stating precisely, because vague claims about compliance are exactly what vendors sell against.
The EU Digital Services Act. The DSA applied to designated Very Large Online Platforms and Very Large Online Search Engines from 25 August 2023, and to the wider set of intermediary services from 17 February 2024. Its operational demands are specific: a notice-and-action mechanism, a statement of reasons for every restriction applied to user content, submission of those statements to the DSA Transparency Database, internal complaint handling, and access to out-of-court dispute settlement. Designated VLOPs additionally run systemic risk assessments, mitigation plans, independent annual audits, and researcher data access. Penalties reach 6 percent of global annual turnover.
Enforcement is no longer theoretical. In July 2026 the European Commission fined AliExpress 550 million euros for DSA breaches, the largest penalty issued under the regulation to date, and issued preliminary findings against TikTok concerning the protection of minors. New designations have continued, with ChatGPT, Reddit, and Roblox brought into scope as of August 2026. In practice a platform now needs a moderation record it can export and defend, not just a filter that works.
The UK Online Safety Act. Ofcom’s illegal content duties and protection of children duties are both in force. In-scope services must complete an illegal content risk assessment and a separate children’s risk assessment, each within three months of launch for new services, and review them annually and before any significant product change. Services must maintain proportionate safety measures, keep records, and operate reporting and complaints routes. Where a service’s principal purpose involves content such as pornography, Ofcom requires highly effective age assurance.
The categorisation regime is the near-term pressure point. Ofcom expects to publish the register of categorised services in July 2026, with Category 1 and Category 2A providers required to submit risk assessment records to Ofcom by October 2026 and publish summaries by November 2026. Enforcement is live: Ofcom fined one adult site 730,000 pounds in September 2026 in connection with age checks.
NCMEC reporting and hash matching. In the United States, 18 U.S.C. 2258A requires electronic communication service and remote computing service providers to report apparent child sexual abuse material to the NCMEC CyberTipline as soon as reasonably possible after obtaining actual knowledge of it, and to preserve the associated material for one year from the date of the report. The statute is explicit that it creates no affirmative duty to monitor users or to search, screen, or scan for violations. Detection is therefore a product decision rather than a legal one, but once a platform detects, reporting becomes mandatory.
That is why the tooling splits into two mechanisms. Hash matching compares perceptual fingerprints of uploaded files against curated databases of previously classified material, which is fast and precise but by definition reactive. Classifier-based detection uses models trained on verified source data to flag content that has never been hashed, including novel and synthetic imagery, and to flag text patterns associated with grooming or exploitation. Most serious programmes run both, route confirmed matches into a reporting workflow, and keep a defensible audit record of who reviewed what and when.
Top Trust And Safety Platforms In 2026
1. Alice — Adversarial Threat Intelligence For Platforms And AI Systems
Alice is the company formerly known as ActiveFence, which rebranded in January 2026 and raised 140 million dollars to extend its work from user-generated content into frontier AI safety and security. The original proposition remains: a research team that tracks adversarial actors across the open and closed web, feeding proprietary intelligence into detection models rather than relying only on customer data. That intelligence covers abuse categories including child safety, terrorism, fraud, and coordinated manipulation across more than 120 languages.
The newer WonderSuite line addresses AI systems directly, with pre-launch stress testing, runtime guardrails for live applications, and continuous red-teaming in production. For a platform shipping both a social product and a generative feature, that removes the need for two separate safety vendors. It is the heaviest option here and priced accordingly, so it suits organisations with a dedicated trust and safety function.
2. Hive — Model-Level Moderation APIs Across Every Modality
Hive sells cloud APIs backed by models trained on proprietary datasets built over close to a decade, covering visual moderation for images and animated formats, text, audio, video, and live stream analysis. A vision language model handles multimodal cases where an image only becomes a violation in combination with its caption. The company also sells AI-generated content detection, which has become a routine requirement for marketplaces and dating products dealing with synthetic profile imagery.
Child safety detection comes through partnerships with Thorn and the Internet Watch Foundation, which matters because credible hash sources are not something a vendor can simply build. Hive publishes tiered pricing and supports custom model development through AutoML, so teams can tune thresholds and add bespoke classes rather than accept a fixed taxonomy. If you want control at the model layer and will build your own review console, start here.
3. Cinder — A Single Operating Console For Every Safety Workflow
Cinder positions itself as the command centre rather than the detector. Policies, review teams, enforcement paths, third-party vendors, and models all sit on one surface, which is the pitch for organisations that have accumulated four tools and a spreadsheet. The platform provides case management, quality assurance, workflow automation, role-based access controls, and audit trails, all of which map directly onto DSA record-keeping expectations.
Its AI agents are configurable decision-makers for content review across adult content, extremism, and CSAM, plus investigation work on coordinated abuse, IP enforcement, account takeover, and fraud. Policy teams build workflows and wire in language models without engineering tickets. The customer base skews toward generative AI companies and fast-growing consumer apps, and the platform carries SOC 2, GDPR, and HIPAA compliance.
4. Checkstep — Moderation Plus DSA Transparency Reporting In One Product
Checkstep combines automated scanning across text, image, video, and audio with human-in-the-loop review and a policy engine, then adds the reporting layer that European platforms need. Statement of reasons generation and transparency reporting are treated as product features rather than a services engagement, which is the main reason mid-market platforms shortlist it over heavier alternatives.
The company runs an open integration model, connecting to third-party classifiers including Amazon Rekognition and OpenAI alongside its own, and maintains a partner network of BPO providers for overflow review capacity. Vertical configurations exist for gaming, marketplaces, streaming, dating, social, and review sites. If your compliance obligations arrived faster than your headcount, Checkstep is built for exactly that gap.
5. Tremau — Regulatory Process Design Backed By A Workflow Platform
Tremau is unusual in pairing software with genuine regulatory advisory. Its Nima platform centralises data signals into a single moderation surface supporting both automated and manual processing, and the surrounding consultancy covers product, engineering, policy, and risk management. The team’s stated focus is compliance with the EU Digital Services Act and the UK Online Safety Act, which reflects where the founders came from.
Named customers include Alibaba, AliExpress, Pinterest, Eventbrite, and Bluesky, covering large marketplaces, established social platforms, and newer decentralised services. That range matters because DSA obligations differ sharply by service type and size. Choose Tremau when the hard part is not detection but designing a notice-and-action process, an appeals route, and a reporting pipeline that holds up under scrutiny.
6. Safer by Thorn — Purpose-Built Child Safety Detection From A Nonprofit
Safer is built by Thorn, a child safety nonprofit, and is the most widely deployed dedicated detection product in this category. It covers known material through proprietary perceptual hashing and previously unseen material through machine learning classifiers, plus a text classifier trained to identify conversations indicative of grooming, sextortion, and exploitation. Thorn reports that Safer has processed more than 1.4 trillion files since 2019.
Deployment is flexible: self-host to limit what data leaves your environment, or integrate via cloud API. Customers include Slack, Vimeo, Patreon, Quora, Bluesky, and Stability AI, and Thorn also runs a consulting practice covering policy and child safety assessments for AI products. Detection here is the input to a reporting obligation, so pair it with a case workflow that preserves evidence and generates a CyberTipline report cleanly.
7. Resolver — Graded CSAM Classification Trained On Law Enforcement Data
Resolver’s Athena product approaches the same problem from a different data source. Alongside hash matching for known material, its classifier is trained on the UK Child Abuse Imagery Database and analyses visual and structural signals to identify characteristics of abuse in content that has never been catalogued, including AI-generated material. It also grades output by category A, B, and C severity, which lets a team prioritise the highest-severity queue rather than treating every flag identically.
Deployment is via API or private cloud with a zero-image-retention policy, and optional specialist review is available for high-confidence flags. Resolver’s broader intelligence line adds online safety compliance tooling and open-web risk monitoring. Severity grading is the differentiator: if review capacity is your constraint, triage quality beats raw recall.
8. Modulate — Real-Time Voice Moderation For Live Communities
Voice remains the least-covered surface in most moderation stacks, and Modulate is the established answer. ToxMod analyses voice channels in real time for harassment, hate speech, and other toxic conduct, using models that weigh tone, emotion, and conversational context rather than transcribing and keyword-matching. Activision is a public reference customer, using the system to identify disruptive behaviour in multiplayer titles.
The company has broadened beyond gaming. Its enterprise platform applies voice intelligence to fraud detection and compliance, and a developer API exposes audio-native models for speech-to-text, deepfake detection, emotion recognition, and music identification, covering more than 150 behaviours in total. Buy it if you run live voice; nothing else here covers that surface as well.
9. Sightengine — Fast, Documented APIs With Broad Class Coverage
Sightengine is the developer-first option. It publishes roughly 150 moderation classes across images and video covering nudity, hate, violence, drugs, weapons, self-harm, and more, alongside text moderation and audio transcription with profanity detection. Its AI content detection suite identifies AI-generated images, deepfake video, synthetic media, and manipulated speech or music, which has become a distinct product line rather than a feature.
Beyond moderation proper, the API set includes near-duplicate detection, QR code scanning, profile image validation, face liveness checks, and OCR for text embedded in images and video. The company emphasises a fully automated pipeline with no human moderator in the loop, which is an advantage for some buyers and a limitation for others. Plan where escalations go before committing.
10. Bodyguard.ai — Real-Time Comment Moderation With Audience Analytics
Bodyguard.ai sits at the intersection of moderation and brand protection. It moderates text for toxicity, spam, and harassment, handles images including memes and screenshots with OCR analysis, and covers video, operating across owned platforms and connected social channels in real time. The company processes billions of comments monthly through native integrations or API.
What distinguishes it is the analytics layer: sentiment analysis, early signal detection for emerging crises, and engagement pattern reporting sit alongside the moderation output. For a sports league, publisher, or consumer brand, the same system that blocks abuse also explains what the audience is doing, which is why it appears in marketing budgets as often as safety ones. It is a weaker fit for platforms whose core product is user-to-user interaction at scale.
How To Choose A Trust And Safety Platform
Are You Buying Detection, Workflow, Or Both?
This is the first fork, and getting it wrong wastes a procurement cycle. Detection vendors such as Hive, Sightengine, and Amazon Rekognition return a classification and a confidence score; what happens next is your problem. Workflow platforms such as Cinder, Checkstep, and Tremau assume signals arrive from somewhere and focus on queues, decisions, appeals, and records. A few do both, but most are stronger at one end. Map your existing stack honestly before shortlisting, because a second detection vendor adds nothing if the real bottleneck is moderators working in a spreadsheet.
Which Content Surfaces Does Your Product Actually Expose?
Audit every surface where a user can put something in front of another user, including the ones nobody owns. Profile photos, display names, direct messages, voice channels, livestreams, uploaded documents, and AI-generated outputs all carry risk, and coverage varies widely. Voice in particular is a specialist requirement that only Modulate addresses at scale. If your product includes a generative feature, you also need prompt and output safety, a different problem handled by a narrower set of vendors.
How Will You Handle Child Safety Detection And Reporting?
Treat this as a separate workstream rather than a checkbox in a general moderation contract. Decide whether you need hash matching against known material, classifier detection of novel and synthetic material, text-based detection of exploitative conversations, or all three. Then design the downstream path before you sign anything: who reviews a flag, how the material is preserved for the statutory one-year period, how a CyberTipline report is generated, and who inside the company is accountable. Vendors including Safer by Thorn and Resolver supply the detection layer, but the reporting obligation and the audit record sit with you.
Can The Platform Produce Evidence A Regulator Will Accept?
Under the DSA a platform must issue a statement of reasons for content restrictions and submit it to the Transparency Database, and under the Online Safety Act it must retain risk assessment and safety measure records. Ask vendors to demonstrate this rather than describe it. Can the system export every decision on a piece of content with timestamps, the policy applied, the reviewer or model responsible, and the appeal outcome? Teams that skip this question discover the gap when the request arrives with a deadline attached.
What Does The Model Do On Your Data, Not Their Benchmark?
Published accuracy figures are measured on vendor datasets and rarely survive contact with a real corpus. Insist on a paid or free pilot against a representative sample of your own content, including the ambiguous cases your moderators argue about. Measure precision and recall separately, because a model that is excellent at recall will bury your review team in false positives. Test the languages, slang, and cultural context your users actually operate in. Ask how the model is retrained, how often, and whether your corrections improve it. This is the same discipline good AI consulting firms apply before any model goes into production.
What Will This Cost To Integrate And Operate?
Licence cost is usually the smaller number. Budget for integration engineering, the moderator hours the system still requires, the quality assurance loop that keeps decisions consistent, and the policy work that precedes all of it. Per-call API pricing looks attractive at low volume and turns unpredictable when a product goes viral, so model your worst month. If integration capacity is the constraint, weigh bringing in a software development partner rather than delaying deployment two quarters.
What Happens When Moderation Fails Publicly?
Every platform eventually ships a decision that becomes a story. Ask whether the vendor gives you the audit trail and the analytics to explain what happened and how quickly it was corrected, because the difference between a contained incident and a sustained one is usually the quality of that record. Platforms that also carry reputational exposure from user content often run this alongside a content removal and suppression capability, but the durable fix is a safety system that produces defensible decisions in the first place.
Conclusion
The trust and safety software market matured quickly, and the 2026 version of it looks different from the 2024 version. Two vendors on the original candidate list for this article had pivoted entirely out of the category, one had been absorbed by a competitor, and the largest name in it had changed its own brand. That churn is worth remembering during procurement: verify a vendor is still selling what you think it sells before you build a roadmap around it.
The practical path is narrower than the vendor count suggests. Establish which surfaces you expose, separate detection from workflow, treat child safety detection and reporting as its own programme with named accountability, and test any model against your own content before signing. Regulatory pressure in the EU and the UK will keep raising the floor on documentation, and US proposals such as the Kids Online Safety Act point the same way, so favour systems that produce a clean record by default. Get those choices right and the logo on the contract matters far less than the operating discipline around it.
If you’re a trust and safety platform and want to feature your company on this list, email us or submit a form in the Top Choices section. After a thorough assessment, we’ll decide whether it’s a valuable addition.
