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What we operate

Five categories. One operating partner for production AI data.

Data annotation services, validation and QA, human-in-the-loop AI operations, back-office data work, and managed data teams. Delivered from a single Nairobi operation, by named teams, at enterprise standards.

Book a discovery call → Explore the stack
ISO 27001 Certified · Cert No. 452AGI102121
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01Annotation & Labeling 02Validation & QA 03HITL AI Operations 04Back-Office Support 05Managed Data Teams

Operating model

Managed teams, not a marketplace.

01 / Lead
Named delivery lead on every engagement
02 / Training
Schema-trained operators, calibrated on gold data
03 / Quality
IAA tracked as a production metric, reported weekly
04 / Security
ISO 27001 ISMS, access-controlled environments

The services

The full stack, under one operation.

From raw annotation through production-grade AI operations, every category is delivered by the same managed team model — trained on your task, accountable to your pipeline.

01/Annotation & Labeling

Data annotation, at production scale.

Our broadest category. Image, video, LiDAR, and text labeled by dedicated teams trained on your schema and held to your accuracy threshold. Six core techniques, one delivery discipline.

Bounding Box
2D object detection, tight-box labelling
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Semantic Segmentation
Pixel-level scene parsing
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Polygonal
Complex shape outlines, instance segmentation
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Video
Frame-by-frame tracking, event annotation
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LiDAR 3D
Point cloud labelling for AV and robotics
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NLP & Text
Entity, intent, sentiment, classification
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Explore Annotation & Labeling →
Polygon pass ● LIVE Polygon annotations outlining vehicles and pedestrians across a purple-lit urban street scene.
IMG_101 · POLYGON_PASS ● Urban scene · Multi-class
02/Validation & QA

Accuracy as a first-class metric.

A self-contained validation operation that plugs into any pipeline — ours or yours. Multi-tier review, inter-annotator agreement scoring, written accuracy guarantees. Applies across every data type we touch.

Quality reports ship every week of delivery — not bolted on at the end of a batch.
Multi-tier Review IAA Scoring Gold-Standard Benchmarking Exception Flagging
Explore Validation & QA →
03/Human-in-the-Loop AI Operations

Ongoing support for production AI systems.

When your model is in production, it still needs human eyes. Content moderation pipelines, AI output review, transcription for training and live ops — run by dedicated teams inside your workflow, not an offshore queue.

Content Moderation Ops
AI output review, policy enforcement, exception handling
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Transcription
Audio to structured text for training and live operations
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Explore HITL AI Operations →
NER pass ● ACTIVE Text annotation interface showing named-entity recognition tags applied across a paragraph.
IMG_103 · NER_REVIEW ● Text pipeline · Tier-1
04/Back-Office Support

Structured data, feeding the pipeline.

The unglamorous but critical layer: structured data operations that feed AI training. Extraction, enrichment, normalization — handled by an operation that treats data hygiene as a deliverable, not a side effect.

Data Entry for AI Pipelines
Structured data operations feeding training datasets
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Explore Back-Office Support →
Bbox batch ● IN REVIEW Bounding-box annotations over a traffic scene — vehicles and pedestrians labeled for downstream training.
IMG_104 · BATCH_0047 ● Structured · Normalized
05/Managed Data Teams

A named team, embedded in your org.

The wrapper around everything else. A dedicated team that behaves as an extension of your AI org — named delivery lead, embedded in your Slack or Linear, continuous delivery model. Not a project. An operation.

“Impact became an operating arm of our data team — not a vendor we manage.”
Named Delivery Lead Client-Embedded Ops Dedicated QA Lead Continuous Delivery Model
Explore Managed Data Teams →
On the floor ● LIVE Two Impact Outsourcing reviewers working together at a laptop during live QA on the Nairobi delivery floor.
IMG_105 · DELIVERY_FLOOR ● Nairobi · Kenya

How engagements work

We scope. Calibrate. Deliver. Continuously.

No spot work. We scope, staff, calibrate, and run continuously as an extension of your AI org — for the lifetime of the engagement.

Phase 01

Discovery

Pipeline review, volume targets, task type. A first conversation that returns something useful either way.

Phase 02

Scope

Schema walk-through, acceptance criteria, security alignment, SOW. Drafted with your data lead.

Phase 03

Calibration

Team trained on your schema and calibrated against gold-standard sets before any production data moves.

Phase 04

Production

Daily throughput with multi-tier QA, weekly IAA reporting, and a named delivery lead in your channels.

Phase 05

Scale

Expand headcount, add workflows, fork specialist subteams — without renegotiating the operating model.

Typical ramp from first call to live production: 3–5 weeks. Calibration is never skipped — it is the reason accuracy holds once we scale.

What we've delivered

Throughput, accuracy, headcount, credentials. Named numbers.

2M+
Records annotated

Delivered for Windward, our longest-running annotation client. Sustained across multiple pipeline generations.

500+
Full-time operators

Trained, calibrated, and retained in Nairobi across annotation, validation, HITL, and back-office teams.

0.94
Average IAA

Inter-annotator agreement averaged across production accounts. Reported weekly, never retrofitted.

6
Production AI clients live

Across computer vision, NLP, and multimodal pipelines. Repeat engagements, not one-off projects.

Scope with us

Send us your pipeline. We'll scope the team.

We read your task schema, your volume requirements, your QA standards. Then we staff and deliver against them — as an extension of your AI org, not a vendor on a queue.

Book a discovery call
30 min · with a delivery lead
→
Email a task brief
contact@impactoutsourcing.co.ke
→

Prefer to start smaller? Run a free trial batch on a slice of your data first.

Request a free trial → About the operation