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Coeus Software

How we helped Coeus Software deploy a secure, police-assured cloud environment on AWS, enabling the delivery of AI-enabled frontline workflows within the UK Police Assured Landing Zone (PALZ)
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  • Public Sector

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  • Scale with Data

Services

  • Cloud Engineering

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Client Context

Coeus Software develops PoliceBox, a frontline application and platform designed to support police officers when information surfaces for action or when officers are collecting information in the field.

PoliceBox provides a secure frontline entry point to multiple back-office and national systems, supports offline working, and is designed around an interoperability-first, open-API architecture rather than bespoke integration. This allows forces to configure and evolve frontline workflows without repeatedly rebuilding underlying systems.

As part of its roadmap, Coeus began developing Project Moriarty, an AI-enabled capability intended to support frontline officers with procedural guidance, particularly in complex or unfamiliar situations. The objective was to support officer judgement and consistency while maintaining strict controls around data sources, assurance and auditability.

The Challenge

UK policing operates in a highly assured technology environment. Any platform handling police data must meet stringent security and governance requirements, including compliance with the Police Assured Landing Zone.

Coeus made a strategic decision to deploy PoliceBox on AWS to support:

  • Scalable, on-demand computing
  • Secure access to managed AI services such as AWS Bedrock
  • Alignment with emerging national cloud patterns across policing

 

PALZ defines required outcomes and controls, but it does not provide a fully prescriptive implementation. Translating those requirements into a working, compliant AWS environment requires deep expertise across networking, identity, permissions and service boundaries.

At the same time, Project Moriarty introduced additional complexity. The AI capability was designed using Retrieval Augmented Generation (RAG), ensuring responses were constrained to approved national and force-specific sources rather than general internet content. This required careful configuration of AWS Bedrock within a tightly controlled environment.

While Coeus had strong product and policing-domain expertise, the organisation did not have sufficient in-house AWS experience to stand up a PALZ-compliant environment quickly enough to support live policing trials.

The Approach

Recognising the need to move quickly without compromising assurance, Coeus engaged Scale Factory as an AWS specialist delivery partner.

Scale Factory worked closely with Coeus to:

  • Set up a fully compliant Police Assured Landing Zone on AWS
  • Deploy the PoliceBox platform within that environment
  • Configure secure access to AWS Bedrock for AI services
  • Implement infrastructure-as-code to automate and repeat the build

 

AWS actively supported the engagement, recognising the strategic importance of enabling assured AI experimentation within policing. AWS funding supported Scale Factory’s involvement, allowing the platform foundation and AI capability to be delivered in parallel.

Outcomes & Impact

The resulting solution provides Coeus with a fully police-assured AWS foundation, designed to be repeatable and scalable.

Project Moriarty uses Retrieval Augmented Generation to provide officers with procedural guidance based exclusively on approved sources, such as national guidance and force documentation. General internet data is deliberately excluded to reduce the risk of incorrect or inappropriate responses.

Scale Factory played a critical role in:

  • Designing a secure network architecture within PALZ
  • Configuring identity and access controls for AI services
  • Ensuring AWS Bedrock operated entirely within the assured boundary
  • Automating the deployment so environments can be recreated consistently

 

By scripting the entire build, Coeus can now spin up a new, compliant backend environment in minutes, supporting future pilots and deployments without repeating foundational work.

The platform supported an NPCC NSIB-funded Test & Learn trial with Humberside Police, integrating AI-driven procedural guidance into frontline workflows.

The work also resolved a common barrier in the policing market: the need for a demonstrably compliant environment before forces are willing to engage seriously with new technology.

simon hall coeus

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01 | Industry challenges discussion

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03 | Solution approach outline

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