Desprings
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AI · Cybersecurity · Digital Transformation · Engineering

Engineering firm · Since 2015

AI and cybersecurity engineering for enterprises that cannot afford failure.

Desprings designs, secures, and operates AI systems and digital platforms for regulated and safety critical industries. Led by engineers with two decades in energy operations, where systems must work the first time.

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Assurance

  • Engineering practice since 2015
  • Led by deepwater and HPHT engineers
  • AI, security, and well engineering

Engagement profile

First phase
Assess, 2 to 3 weeks
Phases
Assess, Pilot, Harden, Operate
Security review
Threat model in the Pilot phase
Works to
NIST AI RMF, NIST CSF 2.0, OWASP

Durations are defaults, agreed for each engagement.

  • 2015

    Established

    Desprings Integrated Limited was established in Lagos, Nigeria, in November 2015.

  • 20

    Years of field experience

    Engineering leadership experience in deepwater and high pressure high temperature well operations.

  • HPHT

    Deepwater completions

    Deepwater and HPHT completions experience: high pressure high temperature wells and gravel pack operations.

01/The problem

Most enterprise AI programs stall between pilot and production.

  1. 01

    Pilots that cannot pass security review

    A model that works in a demo still has to explain its data flows, access paths, and failure modes to your security team. Without that evidence, the pilot never leaves the lab.

  2. 02

    Models without operational ownership

    Once the project team moves on, nobody watches accuracy, drift, or cost. The system degrades quietly until an incident forces a decision.

  3. 03

    Modernization that breaks compliance evidence

    Replatforming changes the systems your auditors already understand. If controls and evidence are not rebuilt with the platform, the next audit becomes the risk.

We build AI and platform work to production, security, and compliance standards from the first week.

What we build

02/Capabilities

Four service lines, held to one engineering standard.

01

AI Engineering

Production AI that passes security review. We design, build, and operate AI systems that run inside regulated and safety critical operations.

Outcomes

  • Pilots taken to production with a named operational owner
  • Threat model and model evaluation report for every system we build
  • Runbooks and a handover your team can operate from

Works to

  • NIST AI RMF
  • ISO/IEC 42001
  • OWASP Top 10 for LLM Applications
AI Engineering service line

02

Cybersecurity

Defense designed around how your systems actually run. We assess, harden, and monitor endpoint, identity, network, and AI system security.

Outcomes

  • An assessment of endpoint, identity, and network exposure
  • Hardening work prioritized by operational risk
  • Monitoring that covers AI systems as well as infrastructure

Works to

  • NIST CSF 2.0
  • CIS Controls
  • MITRE ATT&CK
Cybersecurity service line

03

Enterprise Digital Transformation

Modernization with measurable operational outcomes. We modernize legacy platforms, data estates, and engineering workflows.

Outcomes

  • Legacy platforms modernized without losing compliance evidence
  • Data estates consolidated with clear ownership
  • Engineering workflows measured before and after the change

Works to

  • NIST SSDF (SP 800-218)
  • OWASP ASVS
  • ISO/IEC 25010
Enterprise Digital Transformation service line

04

Engineering and Oil and Gas Solutions

Completions and well engineering from people who have run the operation, for energy operators and service companies.

Outcomes

  • Completions and well engineering consulting
  • Operational support during well programs
  • Project management for energy operators

Operating domains

  • Deepwater
  • High pressure high temperature wells
  • Gravel pack completions
Engineering and Oil and Gas Solutions service line

03/How we engage

Four phases, each with named deliverables.

Each phase has a fixed scope and ends with named deliverables your team keeps. Durations are defaults, agreed for each engagement.

  1. 01 2 to 3 weeks

    Assess

    We map the system, its data, and its risks, then agree what a production pilot must prove.

    Deliverables

    • Architecture risk register
    • Prioritized delivery plan
  2. 02 6 to 10 weeks

    Pilot

    We build the smallest version that runs on real data under real controls.

    Deliverables

    • Working pilot in your environment
    • Threat model
    • Model evaluation report
  3. 03 4 to 8 weeks

    Harden

    We close the findings from your security review and prepare the system for production load.

    Deliverables

    • Closed review findings
    • Monitoring and alerting
    • Rollback procedure
  4. 04 Ongoing

    Operate

    We run the system with your team, or hand it over with everything needed to run it.

    Deliverables

    • Runbook and handover
    • Service reviews
Download capability statement (PDF, 135 KB)

04/Industries

For industries where systems carry regulatory and safety weight.

Energy

Pressures

  • Operational technology that cannot tolerate unplanned downtime
  • Well and asset data spread across contractors and systems
  • Safety cases that must account for every automated decision

Led by engineers with two decades of field experience in deepwater and high pressure high temperature operations.

Energy industry page

Financial Services

Pressures

  • Model risk rules that apply to AI as much as to credit models
  • Legacy core platforms that carry years of audit evidence
  • Supervisors who expect named owners for every control
Financial Services industry page

Telecommunications

Pressures

  • Large, distributed networks with a wide attack surface
  • Subscriber data under national data protection law
  • Operations teams asked to automate without adding outage risk
Telecommunications industry page

Bring us the program your team is worried about.

A senior engineer replies within one business day. The first call is a technical conversation, not a sales presentation.

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