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Data quality: Editorially Reviewed
Language (LLM / NLP)
Government
R&D / applied research services
Model evaluation
Public sector
Red Teaming
Implementation & integration
AI governance, risk & audit
AI & agent security
Predictive / classical ML
Healthcare & life sciences
Computer vision
Cybersecurity
AI security & red-teaming
Services & Consulting
Responsible AI, ethics & safety
AI security
Risk assessment
Aerospace & defense
Enterprise
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Booz Allen Hamilton

Implementation & integration

Offered by Booz Allen Hamilton Inc.

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Overview

Booz Allen's artificial intelligence practice delivers solutions aimed at mission-critical applications across defense, civil government and commercial clients. Public releases describe work protecting machine learning models from data poisoning, leakage, evasion and malicious code injection, backed by an investment in the ML-security platform HiddenLayer. It has also partnered with Credo AI on responsible AI solutions and has held federal AI support contracts such as GSA FEDSIM and the DoD Joint AI Center. The firm, listed on the NYSE as BAH, is based in McLean, Virginia and recently added Ultra I&C Mission Solutions for secure communications and edge computing.

Pricing model
On request
Regions served
North America, Global
Categories
Language (LLM / NLP), Government, R&D / applied research services, Model evaluation, Public sector, Red Teaming, Implementation & integration, AI governance, risk & audit, AI & agent security, Predictive / classical ML, Healthcare & life sciences, Computer vision, Cybersecurity, AI security & red-teaming, Services & Consulting, Responsible AI, ethics & safety, AI security, Risk assessment, Aerospace & defense, Enterprise
Last updated
7 October 2026
Published
7 October 2026

Use cases

AI & agent security
Cybersecurity
Model evaluation
Risk assessment

Data sources & provenance

Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.

Data quality
Data quality: Editorially Reviewed
Sources cited
2
Last reviewed
6 October 2026
Last updated
7 October 2026

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