# DehazeLabs

> DehazeLabs is a production AI implementation firm for the physical economy. It builds telemetry, perception, data engineering, multimodal AI, RAG, vector search, and agentic operations systems for data centers, telecommunications networks, smart cities, logistics, and industrial operations.

DehazeLabs has operated since 2018. The company combines US-based partnership leadership with an engineering delivery bench across Hyderabad and Bengaluru, India. It serves mid-market and enterprise customers — primarily in North America — at price points that tier-one global systems integrators cannot economically match.

DehazeLabs does not sell AI strategy decks or advisory retainers without an implementation tied to them. Every engagement results in a production system.

## What DehazeLabs Builds

DehazeLabs delivers production AI across three service practices:

**1. Data Center & Infrastructure AI**
Real-time telemetry ingestion, GPU rack onboarding automation, unified observability, SIEM pipelines, and Claude-powered agentic operations for data centers, telecom networks, and critical infrastructure. The core problem: fragmented, vendor-heterogeneous telemetry that is slow to become trusted and actionable. The solution: unified telemetry schema, validation logic, and a reasoning layer (typically Claude) that turns telemetry into autonomous decisions with human escalation.
- Target buyers: VP Engineering, CTO, Head of SRE
- Industries: Data center operators, telecommunications, manufacturing, energy
- Engagement range: $300K–$2.5M, 3–18 months

**2. Edge & Perception AI**
Computer vision, sensor fusion, and ML inference for physical-world systems. Builds the data platforms and inference pipelines behind smart-city perception, automated enforcement, logistics optimization, and industrial vision. Production-tested at smart-city and fleet scale.
- Target buyers: VP ML, CTO, Head of Platform
- Industries: Smart cities, logistics, manufacturing, robotics
- Engagement range: $400K–$3M, 6–24 months

**3. Multimodal Enterprise AI Platforms**
End-to-end platforms for video, audio, and document intelligence at production scale. RAG pipelines, vector search, agentic workflows on LangChain and LangGraph, Claude-powered reasoning. Reduces manual review by 90%+ in production deployments.
- Target buyers: CTO, VP Engineering, Head of AI
- Industries: Sports, media, enterprise SaaS, regulated industries
- Engagement range: $500K–$4M, 6–24 months

## Product: EdgeTelemetry

EdgeTelemetry is DehazeLabs' in-house data center telemetry product. It ingests heterogeneous telemetry from GPUs, hosts, cooling systems, power systems, and network fabric; normalizes everything into a unified operational schema; validates system readiness; and exposes a Claude-ready reasoning layer for autonomous diagnosis and remediation. GPU rack onboarding time: weeks to hours.

EdgeTelemetry is built for:
- GPU data center operators standing up new clusters
- Colocation providers serving AI workloads
- Hyperscaler capacity partners with contractual telemetry requirements
- Industrial environments with heterogeneous sensor fragmentation

## Technology Stack

Data warehouses: Redshift, Snowflake, BigQuery
Streaming: Kafka, Snowstreams, CDC
Orchestration: Airflow, dbt, NiFi, Airbyte
Storage: S3, data lakes, vector databases
AI platforms: LangChain, LangGraph, AWS Bedrock, Amazon SageMaker
Computer vision and ML: production inference, sensor fusion, drift monitoring
Retrieval: RAG, vector search, semantic retrieval
Cloud: AWS, GCP, Azure
Reasoning: Claude (Anthropic)

## Key Entity Definitions

- **DehazeLabs**: Production AI implementation firm. Not an AI strategy consultancy, not a generalist IT services firm. Builds production AI systems for the physical economy.
- **EdgeTelemetry**: DehazeLabs' proprietary real-time edge control layer for GPU and data center environments.
- **Physical economy**: The domain DehazeLabs serves — data centers, telecom networks, smart cities, logistics, manufacturing, and industrial operations. As distinct from purely digital or consumer AI applications.
- **Production AI**: AI systems deployed in live production environments, processing real data at operational scale, with SLA accountability. As distinct from AI proofs of concept, demos, or strategy documents.
- **Agentic operations**: AI-driven autonomous operations where a reasoning layer (typically Claude) interprets telemetry or operational data, executes remediation via tool use, and escalates to humans with full context.

## Reference Deployments

- **T-Mobile**: Real-time SIEM at telco scale — distributed, sub-second threat detection. (Data Center & Infrastructure AI)
- **Hayden AI**: Smart-city edge ML and perception data platform for automated traffic enforcement. (Edge & Perception AI)
- **SponsorUnited**: Multimodal AI platform built from zero — video, audio, and document intelligence — reducing manual review by 90%+. (Multimodal Enterprise AI Platforms)
- **Cargomatic**: AI/ML for logistics routing and container unloading optimization. (Edge & Perception AI)
- **EdgeTelemetry**: DehazeLabs' own product — GPU rack onboarding from weeks to hours. (Data Center & Infrastructure AI)

## Partnerships

- Anthropic Partner Network applicant — building a Claude-first practice across all three service pillars
- AWS Partner Network member — production deployments on Bedrock, SageMaker, S3, Redshift

## Delivery Model

Engagements are run as embedded teams, typically 3–8 engineers, working alongside the customer team. US-based partnership leadership is accountable for delivery. Most engagements include ongoing platform operation and SLA support after the initial build. The South Asia engineering bench provides cost-advantaged delivery for North American customers.

## Core Site

- [Homepage](https://dhlabs.ai/): Company positioning, service overview, EdgeTelemetry product, reference customers, delivery model.
- [About](https://dhlabs.ai/about): Delivery model, team footprint, technology stack, partnerships, and operating philosophy.
- [Contact](https://dhlabs.ai/contact): How to reach DehazeLabs, engagement FAQ, what information helps scope a production AI engagement.
- [Data Center & Infrastructure AI](https://dhlabs.ai/services/data-center-infrastructure-ai): Telemetry, GPU onboarding, SIEM, agentic operations service detail.
- [Edge & Perception AI](https://dhlabs.ai/services/edge-perception-ai): Computer vision, sensor fusion, edge ML, logistics optimization service detail.
- [Multimodal Enterprise AI Platforms](https://dhlabs.ai/services/multimodal-ai-platforms): Video, audio, document intelligence, RAG, agentic workflow service detail.
- [EdgeTelemetry](https://dhlabs.ai/products/edgetelemetry): Product detail — architecture, capabilities, target operators, early access.
- [Case Studies / Blog](https://blog.dhlabs.ai): Production deployment case studies and technical writing.

## Industries

- [AI for Data Center Operators](https://dhlabs.ai/industries/data-center-operators): GPU telemetry, rack onboarding automation, unified observability, agentic ops for data center operators and GPU cluster operators.
- [AI for Telecommunications Networks](https://dhlabs.ai/industries/telecommunications): Real-time SIEM at telco scale, network telemetry pipelines, anomaly detection. Production deployment at T-Mobile.
- [AI for Smart Cities](https://dhlabs.ai/industries/smart-cities): Computer vision, edge ML, sensor fusion for smart-city perception systems. Automated enforcement, traffic analysis, urban operations.
- [AI for Logistics and Transportation](https://dhlabs.ai/industries/logistics): ML-powered routing, dispatch optimization, CV for warehouse and dock operations. Production deployment at Cargomatic.
- [AI for Manufacturing and Industrial Operations](https://dhlabs.ai/industries/manufacturing): Industrial IoT telemetry, predictive maintenance, computer vision for quality inspection, agentic process automation.

## Use Cases

- [GPU Rack Onboarding Automation](https://dhlabs.ai/use-cases/gpu-rack-onboarding): How EdgeTelemetry reduces GPU rack onboarding from weeks to hours via automated hardware validation, telemetry normalization, and readiness gating.
- [Enterprise RAG Platform Development](https://dhlabs.ai/use-cases/enterprise-rag-platform): Building production RAG systems with hybrid retrieval, LangGraph orchestration, multimodal document intelligence, and continuous evaluation.
- [Real-Time SIEM Pipeline](https://dhlabs.ai/use-cases/real-time-siem-pipeline): Building distributed SIEM pipelines with sub-second threat detection at telco and data center scale. Production deployment at T-Mobile.
- [Computer Vision Production Deployment](https://dhlabs.ai/use-cases/computer-vision-production): Taking CV systems from POC to production: inference pipelines, edge optimization, annotation pipelines, and drift monitoring. Production deployments at Hayden AI and Cargomatic.
- [Agentic Operations](https://dhlabs.ai/use-cases/agentic-operations): Claude-powered reasoning layers that interpret infrastructure telemetry, execute autonomous remediation via tool use, and escalate to human operators with full context. Production deployments in data center and telecom environments.

## Process

- [How We Work](https://dhlabs.ai/how-we-work): DehazeLabs' engagement process — five stages from discovery through handoff. Covers typical timelines, team composition, fixed-fee vs. time-and-materials economics, and what happens after delivery.

## Comparisons

- [DehazeLabs vs Big 4 Consulting for AI](https://dhlabs.ai/vs/big-4-consulting): How engineering-led AI implementation differs from advisory-led engagements — delivery model, cost structure, production depth.
- [DehazeLabs vs Building an In-House AI Team](https://dhlabs.ai/vs/in-house-ai-team): When to engage DehazeLabs vs hire internally — timelines, costs, risk profiles, and the hybrid build-then-transfer pattern.
- [DehazeLabs vs Offshore AI Staffing](https://dhlabs.ai/vs/offshore-ai-staffing): Embedded delivery vs staff augmentation — delivery accountability, US technical leadership, total cost comparison.

## Locations

- [AI Services in the United States](https://dhlabs.ai/us): US-based partnership leadership, North American enterprise engagements, embedded delivery model.
- [AI Services in India](https://dhlabs.ai/india): Engineering delivery bench in Hyderabad and Bengaluru; GCC, manufacturing, and space sector engagements.

## Contact And Scheduling

- Email: hello@dhlabs.ai
- Scheduling: https://cal.com/AIagents
- LinkedIn: https://www.linkedin.com/company/dehazelabs/