AI
Indika/
SOLUTIONS

Six ways we turn your raw data into a trustworthy asset.

Every engagement starts with the same question: what's actually in your data, and can you trust it? From there, pick the one capability you need or run the full pipeline with us end to end.

6
Core capabilities
1–2 wks
Typical pilot kickoff
98.6%
Avg. labeling accuracy
24/7
Program monitoring
01

Data collection & curation

PROBLEM: data scattered, dirty, unusableFOR: data & ML platform teams

You end up with one clean, governed dataset — deduplicated, PII-scrubbed and unified across text, image, audio, video and sensor sources.

— Multi-source ingestion pipelines (APIs, warehouses, file drops)
— De-duplication, normalization and PII redaction
— Synthetic + real-world data blending for edge cases
Ingestion queueLive
clinical_notes_batch_08.csvCleaned
support_calls_q3.wavTranscribing
warehouse_lidar_set_3Ingesting
Annotation workspace
Warehouse inventory scene
pallet
shelf unit
Bounding boxPolygonKeypoint
02

Annotation & labeling

PROBLEM: unlabeled data blocks every downstream useFOR: ML & product teams

You get production-ready labeled data — boxes, segmentation, NER, transcription, LiDAR — with multi-layer QA and agreement scoring built in.

— Text, image, audio, video, 3D/LiDAR — every modality
— Configurable QA: consensus, gold sets, spot audits
— Your tools or ours — we adapt to existing tooling
Text annotation →Video annotation →

Choosing among data annotation companies

When you compare data annotation companies, look at who does the work, how quality is checked and how your data is handled. Indika AI pairs 60K+ vetted annotators and experts with multi-layer QA, and has processed 2.4M+ items at 99.1% accuracy for 25+ enterprise clients across 10+ industry verticals.

— Certified and compliant: ISO 27001, ISO 9001, SOC 2 and GDPR compliance
— Neutral and independently owned, with no competing house model and no training on client data
— 5+ years in data-centric AI, across text, image, audio, video and 3D/LiDAR
03

Human feedback & evaluation

PROBLEM: no signal on what "good" looks likeFOR: AI product teams

You get structured preference and critique data — vetted experts rank, rate and stress-test outputs against your rubric, turning judgment into a reusable dataset.

— Preference ranking & response comparison at scale
— Adversarial red-teaming & safety evaluation
— Domain-specific rubrics built with subject-matter experts
RLHF data services →
Preference ranking
A · CHOSEN
"Escalate to a specialist given the reported symptom severity."
B
"Suggest rest and monitor symptoms at home."
Rubric: helpfulness · factuality · tone · safety
OnboardingQALabelingRLHFReviewDeploy
Throughput by teamAPI v2.1
04

Data infrastructure & delivery

PROBLEM: labeled data stuck outside your pipelineFOR: data engineering teams

You get structured data landing directly where you need it — QA reports and APIs that plug straight into your existing systems.

— 100+ pre-built applications across common use cases
— Full API access for programmatic task management
— Custom-built interfaces for novel task types
05

Data quality monitoring

PROBLEM: data drifts silently after launchFOR: MLOps & data teams

You get continuous visibility into your data's health — drift detection and human review loops catch quality issues before they reach users.

— Production quality monitoring & drift detection
— Ongoing human review loops for edge cases
Data quality signals● Live
99.2%
Precision
0.4%
Drift (7d)
212ms
Eval latency
Tax attorneyMatched
ICU nurse practitionerMatched
Quant researcherScreening
06

Specialized expert network

For tasks needing judgment, not just attention — matched to verified physicians, lawyers, engineers and analysts.

Scope an expert-led project →

Why enterprises choose Indika over a point solution

1
One vendor, full lifecycle
No handoffs between collection, labeling, RLHF and deployment teams.
2
Verified domain experts
Real clinicians, lawyers and engineers, not anonymous crowdwork.
3
Audited, compliant delivery
ISO, SOC 2 and GDPR aligned from day one, not bolted on later.
4
Transparent pricing
Scoped pilots and clear per-task or program-based pricing.

Frequently asked questions

Can we start with a single solution and expand later?
+
Yes — most programs start with one capability (often annotation or RLHF) and expand into collection or deployment monitoring as the program matures.
How fast can a pilot start?
+
Do you support our existing annotation tools?
+
How do you vet domain experts?
+
FIND YOUR FIT

Not sure where to start? Answer two questions.

1 of 2 — What kind of data are you working with?
Text
Image / Video
Audio
Multimodal / mixed
Other
ESTIMATE YOUR PROGRAM

What would a data program cost at your scale?

Monthly items to label50K–250K
Modalities involvedTwo modalities
$20K–60K/mo
Estimated monthly range
3 weeks
Typical pilot-to-scale timeline
Directional estimate — final pricing scoped per engagement.

Not sure which solution fits your program?

Tell us your data, modality and timeline — we'll scope the right mix.

Talk to our team →
AI
Indika/

The data foundation enterprises trust to build reliable AI, since 2021.

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