Managed Automation Services & Data labeling for Enterprise AI

document automation
Expert data annotators governed by platform-led HITL, with gold sets, consensus checks, and review guidelines, delivering faster turnarounds, measurable accuracy, and audit-ready training datasets.
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Reliable labeling at scale, without quality drift

Not gig. Top 1% domain-vetted data annotation teams governed by playbooks, QA, and visible metrics, so scale never melts quality.
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Domain-vetted specialists
Specialists are matched to your ontology across medical, fintech, retail, and geospatial domains. They calibrate to IAA ≥ 0.85 before going live and follow defined QC methods and hierarchical adjudication.
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Rapid project execution
Start with a 48-hour pilot that maps the ontology, creates gold examples, and runs a calibrated sample sprint. A dedicated engagement manager, clear SLAs, and fast email and Slack support keep work moving without accuracy slipping.
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Best-in-class data annotation tool
Workflows use QC methods, maker-checker review, including gold sets, and consensus sampling. A clean UI with hotkeys, pixel-level tools, and clear reviewer queues. Access is secured with SSO and RBAC, and S3, GCS, and Azure integrations with exports in COCO, YOLO, VOC, and JSONL, plus audit logs.
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Efficiency gains
Post calibration, teams see 30 to 50% fewer reworks and 20 to 40% faster handling. The cost per accepted item falls, and per-class accuracy remains within the signed acceptance bands.

Multimodal data collection & annotation services

Enterprise data annotation services powered by human-in-the-loop data labeling and platform QA, so training datasets behave in production and pass audits.
built scale
Images
Image annotation for model training: class labels, boxes, polygons, masks, keypoints, and attributes using a defined ontology, gold examples, and maker–checker review. Deliverables include COCO, YOLO, or Pascal VOC files with QA status.
built scale
Video
Video annotation services for production use: frame labeling, identity tracking, action and event tagging, and temporal consistency checks with adjudication when needed. Deliverables include per-track timelines, timestamps, confidence values, and reviewer notes.
built scale
Text
Text annotation services for NLP workloads: intent, sentiment, safety or toxicity, classification, and NER with span offsets using clear rubrics and multilingual review. Deliverables include JSONL files containing entities, relations, confidence scores, and reviewer outcomes.
built scale
Documents
Document annotation for Document AI pipelines: field extraction, format validation, normalization, and redaction by default using OCR or ICR. Deliverables include structured JSON with full provenance and an auditable change log.
built scale
Audio
Audio labeling for ASR and voice models: timestamped transcripts, speaker diarization, and intent or emotion tags with escalation for unclear segments. Deliverables include segments, speaker IDs, label confidence, and WER or CER metrics.
built scale
3D / Sensor
LiDAR and 3D sensor annotation for autonomy and mapping: 3D boxes, polygons, trajectories, and sensor fusion alignment validated against IoU and temporal targets. Exports support KITTI, Waymo-style, or custom JSON.
built scale
Images
Image annotation for model training: class labels, boxes, polygons, masks, keypoints, and attributes using a defined ontology, gold examples, and maker–checker review. Deliverables include COCO, YOLO, or Pascal VOC files with QA status.
built scale
Video
Video annotation services for production use: frame labeling, identity tracking, action and event tagging, and temporal consistency checks with adjudication when needed. Deliverables include per-track timelines, timestamps, confidence values, and reviewer notes.
built scale
Text
Text annotation services for NLP workloads: intent, sentiment, safety or toxicity, classification, and NER with span offsets using clear rubrics and multilingual review. Deliverables include JSONL files containing entities, relations, confidence scores, and reviewer outcomes.
built scale
Documents
Document annotation for Document AI pipelines: field extraction, format validation, normalization, and redaction by default using OCR or ICR. Deliverables include structured JSON with full provenance and an auditable change log.
built scale
Audio
Audio labeling for ASR and voice models: timestamped transcripts, speaker diarization, and intent or emotion tags with escalation for unclear segments. Deliverables include segments, speaker IDs, label confidence, and WER or CER metrics.
built scale
3D / Sensor
LiDAR and 3D sensor annotation for autonomy and mapping: 3D boxes, polygons, trajectories, and sensor fusion alignment validated against IoU and temporal targets. Exports support KITTI, Waymo-style, or custom JSON.
built scale
Images
Image annotation for model training: class labels, boxes, polygons, masks, keypoints, and attributes using a defined ontology, gold examples, and maker–checker review. Deliverables include COCO, YOLO, or Pascal VOC files with QA status.
built scale
Video
Video annotation services for production use: frame labeling, identity tracking, action and event tagging, and temporal consistency checks with adjudication when needed. Deliverables include per-track timelines, timestamps, confidence values, and reviewer notes.
built scale
Text
Text annotation services for NLP workloads: intent, sentiment, safety or toxicity, classification, and NER with span offsets using clear rubrics and multilingual review. Deliverables include JSONL files containing entities, relations, confidence scores, and reviewer outcomes.
built scale
Documents
Document annotation for Document AI pipelines: field extraction, format validation, normalization, and redaction by default using OCR or ICR. Deliverables include structured JSON with full provenance and an auditable change log.
built scale
Audio
Audio labeling for ASR and voice models: timestamped transcripts, speaker diarization, and intent or emotion tags with escalation for unclear segments. Deliverables include segments, speaker IDs, label confidence, and WER or CER metrics.
built scale
3D / Sensor
LiDAR and 3D sensor annotation for autonomy and mapping: 3D boxes, polygons, trajectories, and sensor fusion alignment validated against IoU and temporal targets. Exports support KITTI, Waymo-style, or custom JSON.
built scale
Images
Image annotation for model training: class labels, boxes, polygons, masks, keypoints, and attributes using a defined ontology, gold examples, and maker–checker review. Deliverables include COCO, YOLO, or Pascal VOC files with QA status.
built scale
Video
Video annotation services for production use: frame labeling, identity tracking, action and event tagging, and temporal consistency checks with adjudication when needed. Deliverables include per-track timelines, timestamps, confidence values, and reviewer notes.
built scale
Text
Text annotation services for NLP workloads: intent, sentiment, safety or toxicity, classification, and NER with span offsets using clear rubrics and multilingual review. Deliverables include JSONL files containing entities, relations, confidence scores, and reviewer outcomes.
built scale
Documents
Document annotation for Document AI pipelines: field extraction, format validation, normalization, and redaction by default using OCR or ICR. Deliverables include structured JSON with full provenance and an auditable change log.
built scale
Audio
Audio labeling for ASR and voice models: timestamped transcripts, speaker diarization, and intent or emotion tags with escalation for unclear segments. Deliverables include segments, speaker IDs, label confidence, and WER or CER metrics.
built scale
3D / Sensor
LiDAR and 3D sensor annotation for autonomy and mapping: 3D boxes, polygons, trajectories, and sensor fusion alignment validated against IoU and temporal targets. Exports support KITTI, Waymo-style, or custom JSON.

An arsenal of capabilities, built for production-grade AI pipelines

Platform-governed HITL, Nimble data collection, and governed workflows that deliver measurable, repeatable training-data quality.
TALK TO OUR EXPERTS
geospatial
Managed annotation for CV, NLP, document, audio, geospatial, and LLMs
Human-in-the-loop data labeling with gold sets, consensus sampling, adjudication, and per-class review intensity. Calibration reduces rework by 30-50% and keeps acceptance criteria repeatable across sprints.
real time
Real-time edge-case resolution
Escalation queues route tricky items to senior reviewers quickly. Resolution notes feed back into rubrics, cutting recurring errors and stabilizing per-class accuracy variance.
domain
Domain-centric AI model evaluation
AI model evaluation services tailored to your domain. Calibrated raters score helpfulness, faithfulness, safety, and task success using clear rubrics, pairwise preferences, and audit-ready reports.
nimble
Nimble: enterprise data collection for multimodal AI
Capture images, video, text, documents, audio, and 3D sensors with consent workflows and versioned uploads. Every sample is traceable, compliant, and ready for downstream labeling and review.
localization
Localization and translation labeling
Multilingual operators capture intent, entities, and tone in more than 25 languages. Regional reviews ensure cultural accuracy, so models behave correctly in production.
auto qa
Auto-QA and drift control
Programmatic checks validate structure and logic. Scheduled gold refresh and drift alerts trigger targeted re-reviews to keep accuracy within the acceptance thresholds you signed.
geospatial
Managed annotation for CV, NLP, document, audio, geospatial, and LLMs
Human-in-the-loop data labeling with gold sets, consensus sampling, adjudication, and per-class review intensity. Calibration reduces rework by 30-50% and keeps acceptance criteria repeatable across sprints.
real time
Real-time edge-case resolution
Escalation queues route tricky items to senior reviewers quickly. Resolution notes feed back into rubrics, cutting recurring errors and stabilizing per-class accuracy variance.
domain
Domain-centric AI model evaluation
AI model evaluation services tailored to your domain. Calibrated raters score helpfulness, faithfulness, safety, and task success using clear rubrics, pairwise preferences, and audit-ready reports.
nimble
Nimble: enterprise data collection for multimodal AI
Capture images, video, text, documents, audio, and 3D sensors with consent workflows and versioned uploads. Every sample is traceable, compliant, and ready for downstream labeling and review.
localisation
Localization and translation labeling
Multilingual operators capture intent, entities, and tone in more than 25 languages. Regional reviews ensure cultural accuracy, so models behave correctly in production.
auto qa
Auto-QA and drift control
Programmatic checks validate structure and logic. Scheduled gold refresh and drift alerts trigger targeted re-reviews to keep accuracy within the acceptance thresholds you signed.

Your documents, decoded in seconds. One platform for hundreds of industry use cases.

Read, validate, and export complex documents at scale: layout-aware OCR, field checks, and reviewer queues that keep finance, insurance, and tax workflows effective.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
BFSI & Fintech
KYC/AML, statements, onboarding, and risk docs. Human reviewers extract, validate, and reconcile fields with redaction by default, along with audit-ready trails and SLAs aligned to compliance windows.
built scale
Healthcare
DICOM, pathology, and clinical notes. Clinician-in-the-loop pipelines with PHI masking, double review on critical classes, and adjudication to keep study consistency stable across cohorts and versions.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
Geospatial
Satellite, aerial, and street-level imagery. Segmentation, change detection, and feature extraction at tile scale, with versioned datasets and per-class QA intensity across seasons and sensors.
built scale
LLMs & AI Agents
RLHF, pairwise preferences, rubric evaluations, and safety red-teaming. Leakage-guarded queues and calibrated raters ensure that preference signals remain consistent as prompts, policies, and tools evolve.
built scale
Industrial / Manufacturing
Defect detection, OCR QC, and anomaly labeling. Plant-floor-friendly workflows with controlled access, uptime commitments, and per-class review intensity to balance throughput with traceable quality.
built scale
Insurance
Claims triage, damage assessment, and forms extraction. Calibrated rubrics, escalation queues, and audit trails minimize adjuster back-and-forth while maintaining accuracy at peak volumes.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
BFSI & Fintech
KYC/AML, statements, onboarding, and risk docs. Human reviewers extract, validate, and reconcile fields with redaction by default, along with audit-ready trails and SLAs aligned to compliance windows.
built scale
Healthcare
DICOM, pathology, and clinical notes. Clinician-in-the-loop pipelines with PHI masking, double review on critical classes, and adjudication to keep study consistency stable across cohorts and versions.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
Geospatial
Satellite, aerial, and street-level imagery. Segmentation, change detection, and feature extraction at tile scale, with versioned datasets and per-class QA intensity across seasons and sensors.
built scale
LLMs & AI Agents
RLHF, pairwise preferences, rubric evaluations, and safety red-teaming. Leakage-guarded queues and calibrated raters ensure that preference signals remain consistent as prompts, policies, and tools evolve.
built scale
Industrial / Manufacturing
Defect detection, OCR QC, and anomaly labeling. Plant-floor-friendly workflows with controlled access, uptime commitments, and per-class review intensity to balance throughput with traceable quality.
built scale
Insurance
Claims triage, damage assessment, and forms extraction. Calibrated rubrics, escalation queues, and audit trails minimize adjuster back-and-forth while maintaining accuracy at peak volumes.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
BFSI & Fintech
KYC/AML, statements, onboarding, and risk docs. Human reviewers extract, validate, and reconcile fields with redaction by default, along with audit-ready trails and SLAs aligned to compliance windows.
built scale
Healthcare
DICOM, pathology, and clinical notes. Clinician-in-the-loop pipelines with PHI masking, double review on critical classes, and adjudication to keep study consistency stable across cohorts and versions.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
Geospatial
Satellite, aerial, and street-level imagery. Segmentation, change detection, and feature extraction at tile scale, with versioned datasets and per-class QA intensity across seasons and sensors.
built scale
LLMs & AI Agents
RLHF, pairwise preferences, rubric evaluations, and safety red-teaming. Leakage-guarded queues and calibrated raters ensure that preference signals remain consistent as prompts, policies, and tools evolve.
built scale
Industrial / Manufacturing
Defect detection, OCR QC, and anomaly labeling. Plant-floor-friendly workflows with controlled access, uptime commitments, and per-class review intensity to balance throughput with traceable quality.
built scale
Insurance
Claims triage, damage assessment, and forms extraction. Calibrated rubrics, escalation queues, and audit trails minimize adjuster back-and-forth while maintaining accuracy at peak volumes.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
BFSI & Fintech
KYC/AML, statements, onboarding, and risk docs. Human reviewers extract, validate, and reconcile fields with redaction by default, along with audit-ready trails and SLAs aligned to compliance windows.
built scale
Healthcare
DICOM, pathology, and clinical notes. Clinician-in-the-loop pipelines with PHI masking, double review on critical classes, and adjudication to keep study consistency stable across cohorts and versions.
built scale
E-commerce & Retail
Search relevance, catalog taxonomy, attributes, and UGC safety. HITL teams curate clean product data and judgments, ensuring that discovery, recommendations, and merchandising behave as customers expect.
built scale
Geospatial
Satellite, aerial, and street-level imagery. Segmentation, change detection, and feature extraction at tile scale, with versioned datasets and per-class QA intensity across seasons and sensors.
built scale
LLMs & AI Agents
RLHF, pairwise preferences, rubric evaluations, and safety red-teaming. Leakage-guarded queues and calibrated raters ensure that preference signals remain consistent as prompts, policies, and tools evolve.
built scale
Industrial / Manufacturing
Defect detection, OCR QC, and anomaly labeling. Plant-floor-friendly workflows with controlled access, uptime commitments, and per-class review intensity to balance throughput with traceable quality.
built scale
Insurance
Claims triage, damage assessment, and forms extraction. Calibrated rubrics, escalation queues, and audit trails minimize adjuster back-and-forth while maintaining accuracy at peak volumes.

How we run managed data labeling projects

Clear owners, governed workflows, and measurable exits at every stage.
scoping
Project Scoping & Ontology Design
Define classes, SLAs, risks, edge cases, and data flows together. The phase ends when the versioned ontology, rubrics, escalation paths is approved.
pilot
Pilot & calibration
We label sample data provided by you to tune rubrics and coaching. Go-live is gated on an agreed IAA target for critical classes (for example, ≥0.85) and a stable error taxonomy. You sign off only after the metrics hold steady.
embedded
Production with embedded QA
Follow-the-sun pods execute with per-class review intensity, consensus sampling, and automated checks. Disagreements move through an adjudication ladder, and drift alerts trigger targeted re-reviews. Throughput increases without letting accuracy slide.
continuous
Reporting & continuous improvement
Live dashboards track IAA by class, handle time, cost per asset, and review intensity. Weekly ops reviews translate numbers into concrete actions for the next sprint. You see exactly what we see, in real time.
scoping
Project Scoping & Ontology Design
Define classes, SLAs, risks, edge cases, and data flows together. The phase ends when the versioned ontology, rubrics, escalation paths is approved.
pilot
Pilot & calibration
We label sample data provided by you to tune rubrics and coaching. Go-live is gated on an agreed IAA target for critical classes (for example, ≥0.85) and a stable error taxonomy. You sign off only after the metrics hold steady.
embedded
Production with embedded QA
Follow-the-sun pods execute with per-class review intensity, consensus sampling, and automated checks. Disagreements move through an adjudication ladder, and drift alerts trigger targeted re-reviews. Throughput increases without letting accuracy slide.
continuous
Reporting & continuous improvement
Live dashboards track IAA by class, handle time, cost per asset, and review intensity. Weekly ops reviews translate numbers into concrete actions for the next sprint. You see exactly what we see, in real time.

Expert annotation services for document automation

Pair Taskmonk’s tooling with an expert workforce to label at speed, hold quality steady, and turn documents into export-ready data—without adding headcount or duct-taping vendors.
TALK TO OUR EXPERTS
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Accuracy you can accept
Per-class acceptance thresholds are defined in the pilot and locked before go-live. If a batch misses the threshold, we rework it at our cost with root-cause notes and fixed rubrics.
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Throughput without the drama
We commit TAT bands, reviewer hours, and follow-the-sun coverage for predictable daily velocity. If queues slip, items auto-requeue by priority and leads intervene before deadlines become accuracy debt.
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Security and compliance, by default
SSO, RBAC, PII/PHI masking, and full audit logs. DPAs/BAAs as needed. Data stays in approved regions with least-privilege, attributable access.
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Radical transparency
Live dashboards show cost/asset, IAA, review intensity, and drift. Rubrics are versioned with changelogs, so budgets map cleanly to delivered outcomes.
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Single-threaded ownership
A dedicated engagement manager and QA lead run your pod. The team remains intact across sprints, with weekly operations reviews and clearly defined follow-ups.
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Responsible AI, in practice
Your Models Deserve Better Training Data. Let’s Fix That. We document decisions, escalate edge cases, and avoid training on sensitive signals.

FAQ

What are managed data labeling services?
Managed data labeling services deliver end-to-end HITL operations—workforce, QA, tooling, dashboards, and SLAs—with a single accountable owner, producing production-ready datasets for enterprise AI programs.
How do you measure and guarantee quality?
We conduct data labeling QA with per-class SLAs, including pilot IAA ≥ 0.85, gold sets, consensus sampling, adjudication ladders, and root-cause rework, all performed at our cost.
How quick can we start?
Start with a 48-hour pilot: map the ontology, create a gold set, and run a calibrated HITL sample sprint. If the metrics hold, we begin production under SLAs.
How do you handle PHI/PII and compliance?
We secure PHI/PII with SSO, RBAC, and redaction by default, along with full audit logs. DPAs/BAAs are signed, data residency is honored, and least-privilege access is enforced throughout.
How do you ensure annotators follow directions and don’t game metrics?
We use paid test tasks, calibration gates, IAA targets, and supervision with audit trails—aligning incentives to quality rather than raw throughput.

Expert human evalutions of your AI models

Reach out to our team to assess your use case and see how we run managed data annotation projects.
TALK TO OUR EXPERTS
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