The Multimodal Data Annotation that F500 Enterprises Run in Production AI

Proven on 900M+ transactions with 99.9% uptime. AI pre-labeling, workflow orchestration and qualified human experts, delivering image, video, text, audio, document, LiDAR and DICOM data in one platform.

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Features that keep multimodal data programs moving

One system to label, check and ship multimodal data across images, video, text, audio, documents and LiDAR.

One labeling interface for every data type

Purpose-built tools for image, video, text, audio, document, LiDAR, DICOM and geospatial work, all in one workspace.

Linked, cross-modal tasks

Transition automatically between projects across modalities. Use transcribed audio text in NER projects, and support point cloud and video together in LiDAR.

Multimodal datasets and batches

Split large imports into batches, track each through its lifecycle, then browse, search and download results in Gallery view.

Collaboration and integrations

Comments on rejected tasks and rule-based task assignment keep teams aligned. Connect your stack through the REST API and Python or Java SDKs.

One workflow for every data type

Set up tasks, routing and review once that work across image, video, text, audio, LiDAR and DICOM work with the same quality rules.

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Build the workflow

Define tasks, roles, routing and pass criteria, then connect annotate, review and consensus stages without code. Configure projects to flow between data types, so the output of one feeds the next.

Label, review, adjudicate

Start from pre-labels, with tracking and interpolation for video and OCR or speech-to-text for documents and audio. Disagreements go to a reviewer, and execution levels stop batches that miss quality thresholds

Export

Export to S3, GCS or Azure in COCO, YOLO, Pascal VOC, JSON, JSONL or CSV, straight into your training pipeline. A time-stamped audit trail records who labeled, edited and approved each task.

Secure multimodal workflows at scale

Your data stays in your cloud, behind enterprise access controls.

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Access & authentication

Two-factor sign-in, role-based access, IP allowlisting and secure credential management, with controls down to class level by execution level.

Compliance

Hosted on Azure data centers that are SOC 2, ISO 27001 and HITRUST compliant, with HIPAA and GDPR alignment.

Deployment

Run in a dedicated VPC, or connect your S3, Azure or GCS buckets with signed URLs so the originals never move.

Multimodal data labeling for any use case

Run workflows on the platform or with Taskmonk experts. Start fast, keep quality measurable, ship on schedule.

Vision and language

Link phrases to boxes or polygons on images and video frames. Export datasets for captioning, referring expressions and visual question answering.

E-commerce product data

Match images to SKUs, pull attributes from titles and specs, and normalize taxonomy so product pages stay consistent and searchable.

Speech analytics

Transcribe audio, split speakers and timestamp phrases. Tag intent, emotion and sensitive content, then export segment-level datasets.

LiDAR and geospatial

Label boxes, keypoints and masks on multi-camera video aligned to point clouds, and geo-tag satellite imagery and maps.

Healthcare imaging

Label findings on DICOM, NIfTI and whole-slide images, and link report text to image evidence, with HIPAA-aligned access.

Human evaluation & RLHF

Rank preferences and score model responses across text, image, video and audio tasks. Export rankings and rationales for fine-tuning.

Start with the data type you label most

Image, video, text, audio, LiDAR and DICOM work runs on the same workflow, QA and security, with tools built for each.

Image annotation

Draw boxes, polygons and keypoints, or segment an object with one click. YOLO pre-labels start each task, and COCO, YOLO and Pascal VOC exports go straight to training.

Video annotation

Label key frames and let interpolation and object tracking carry the labels across the frames between them, for boxes, keypoints and segmentation.

Text annotation

Tag entities, intent and sentiment on custom screens built without code, with NER pre-labeling to speed up the first pass.

Audio annotation

Transcribe with Whisper or Google speech-to-text pre-labels, split speakers, tag emotion and timestamp each segment.

LiDAR

Label objects in 3D point clouds with multi-camera sync and top, side and front views, so each object lines up with its camera image.

DICOM

Label findings on DICOM, NIfTI and whole-slide images in 2D, 3D and 4D views, with window and level presets and HIPAA-aligned access.

Document automation

Turn invoices, forms & PDFs into structured fields with OCR and Mistral OCR pre-labels, then have humans check and normalize.

Geospatial

Geo-tag and label satellite and aerial imagery and maps with precise coordinates.

Voice AI

Annotate calls and voice-agent conversations with transcripts, speakers, intent and emotion, and plug in your own speech recognition models.

One platform, three pillars

AI pre-labeling, workflow orchestration and qualified human experts work as one execution layer for multimodal data.

AI Pre-Labeling

Models draft the labels, so experts start from a pre-filled task instead of a blank one. SAM-3 segmentation, YOLO detection, Mistral OCR, Whisper and Google speech-to-text run out of the box, and your own models plug in.

Workflow Orchestration

Tasks, roles, routing and review stages are set up without code and run the same way for every data type. Maker-Checker, consensus and golden sets are built into each workflow.

Qualified human experts

Experts are assessed, trained, certified and monitored before they enter production, across 20+ languages and teams that scale from 18 to 1,200+ associates.

Proven in production: 900M+ transactions and 10+ years of delivery

Results across image, video, LiDAR and audio programs, with 99.9% uptime on Azure and 7M+ labeling hours.

CASE STUDY

A global e-commerce platform reached 99%+ search relevance.

Autonomous robots

LiDAR point cloud annotation for autonomous mobile robots.

Retail video AI

A global retailer cut checkout shrinkage by 38% with video annotation.

Indic audio

A US AI research company reached 90%+ accuracy across 9 Indic languages.

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Multimodal data annotation services, run by qualified experts

A trained team builds your multimodal AI training data on the Taskmonk platform, with measurable QA and SLAs from the first batch.

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End-to-end project management

Scoping, guidelines, workflow setup, staffing and QA run through delivery, with one point of contact.

Qualified experts

Experts are screened, trained and certified on your guidelines, then tested on sample tasks. Only qualified experts enter production.

Teams that scale

Vetted Teams that scale with you for AI projects across data types & industries as your volume changes

Industry-trained experts

Domain-qualified experts for e-commerce, healthcare, finance, legal, automotive and physical AI, and customer service programs.

Fixed quotes

Managed services are scoped per project, with a fixed quote and a delivery timeline agreed before any work begins.

Proof of concept

Share a sample dataset and guidelines. A workflow is set up, annotators are assigned and labeled samples return with a QA snapshot in 24 to 48 hours.

Go deeper on multimodal annotation

Guides & playbooks on choosing a platform, LiDAR, documents, medical imaging, robotics and outsourcing.

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View all Blogs

FAQ

What is multimodal data annotation?

Multimodal data annotation labels more than one data type together, such as images with text or video with audio, and keeps the links between them aligned. It builds the training data for models that learn from several inputs at once.

Which data types can Taskmonk label in one platform?

Image, video, text, audio, document, LiDAR, DICOM and geospatial data run on one platform, with shared workflows and QA.

How does pre-labeling work across data types?

Models pre-label the data: SAM-3 for segmentation, Mistral OCR for documents, Whisper and Google speech-to-text for audio, and your own models. Experts review the output before export.

How is quality kept consistent across data types?

Maker-Checker, consensus and golden tasks apply to every data type, with expert arbitration on ambiguous cases.

What export formats and integrations are available?

Export COCO, YOLO, Pascal VOC or JSON, write results to S3, GCS or Azure, and connect through the REST API and Python or Java SDKs.

How are annotators vetted and onboarded?

Experts are screened, assessed on skills and domain knowledge, trained on your guidelines and certified on sample tasks. Only certified experts enter production, and gold tasks track their accuracy.

Can Taskmonk run in our cloud?

Yes. Projects can run in a dedicated VPC, with data read from your own S3, Azure or GCS buckets.

Does Taskmonk support RLHF and model evaluation data?

Yes. Build preference-ranking and response-evaluation tasks across text, image, video and audio, and export the results for alignment and fine-tuning.

How is pricing structured?

Platform access is $60 per active user per month, billed only for seats used that month. Managed annotation services are scoped per project with a fixed quote before work starts.

How do we start?

Start with a proof of concept: share a sample dataset and guidelines, and labeled samples return with a QA snapshot in 24 to 48 hours.

See your multimodal workflow in action

Share a small dataset and goals. A workflow is configured, a subset labeled, and a QA snapshot returned within 24 to 48 hours

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The Multimodal Data Annotation that F500 Enterprises Run in Production AI

Features that keep multimodal data programs moving

One workflow for every data type

Secure multimodal workflows at scale

Multimodal data labeling for any use case

Start with the data type you label most

One platform, three pillars

Proven in production: 900M+ transactions and 10+ years of delivery

Multimodal data annotation services, run by qualified experts

Go deeper on multimodal annotation

FAQ

See your multimodal workflow in action

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