Production assurance and engineering for software that now matters.
Know what you can rely on.Build what comes next.
You proved the product. Now the engineering has to carry what comes next.
Lornets establishes what the business can depend on, strengthens what genuinely needs to change and builds new production capabilities where the next step calls for it.
Assess first. Keep what works. Change only what the evidence justifies.
Assurance, engineering and forward engineering, under one discipline.
Lornets is not a general development agency and not an AI consultancy. The same evidence-led discipline runs across assessing what exists, strengthening what needs to change and building what comes next.
01
Know what you can rely on
Assess what is already there and establish what the business can safely depend on.
02
Strengthen what matters
Harden, refactor, transition or support the software where the evidence shows that change is justified.
03
Build what comes next
Take defined AI use cases, agents, automation and other new capabilities into production.
The engineering question changes when the software becomes important.
Once customers, revenue, sensitive data, investors or critical operations depend on the software, “it works” is no longer the whole question.
Rapid development can establish that a product is useful. It does not by itself establish whether the organisation can depend on the system under its next operating conditions.
When to bring us in
- The product has become important to the business
- A serious customer is scrutinising the technology
- Fundraising or technical diligence is approaching
- A major rewrite or migration is being proposed
- The system is beginning to show strain
- An AI use case needs to move into real operations
- The organisation needs ongoing production stewardship
The question is no longer only “does it work?” It becomes “what can we substantiate, what is actually constrained, and what change is justified?”
For organisations where software carries real consequences.
- Software companies entering a more demanding stage
Products approaching fundraising, greater scale, enterprise scrutiny or increased operational dependence.
- Businesses becoming dependent on internally built software
Organisations whose internal or commissioned systems now carry meaningful operational, customer or data responsibility.
- Organisations adopting AI in real operations
Teams moving a consequential AI use case from experimentation into a workflow the organisation needs to depend on.
The same software can face very different business questions.
We do not begin by selling development capacity. We establish the technical position first, then strengthen, transition, deploy or support only where the evidence justifies it.
01
Assess
Can the organisation depend on this software for what it needs to do next?
Where most engagements start
02
Substantiate
When a customer, investor or other external party starts scrutinising the technology, Lornets focuses the assessment on the claims and evidence that matter to that decision.
- Enterprise ReadinessTechnical assurance for organisations entering enterprise procurement or customer scrutiny, including customer requirements, evidence readiness and material procurement blockers.
- Fundraise Technical ReadinessAn independent view of the technical position before diligence: what can be substantiated, what deserves attention and what management should be ready to explain.
03
Change
When evidence identifies a material constraint, or a new capability is justified, Lornets implements the smallest defensible engineering response.
- Production Hardening & ScaleEvidence-led engineering for systems that need stronger reliability, security, operational resilience or measured scale. Keep what works, change what is justified and verify the result.
- Platform Transition & MigrationAn independent decision engagement resolving to Stay, Refactor, Hybrid or Migrate, followed by transition engineering only where substantial change is justified.
- Forward Deployed AI EngineeringSenior engineering placed inside the organisation to take a defined AI use case from intent to a measurable capability running in production.
04
Operate
As the system changes, the assurance position can change with it. Managed Production Engineering maintains evidence, verifies material changes and addresses assurance drift.
FUNDRAISE TECHNICAL READINESS
Know the technical position before diligence establishes it for you.
Fundraising is one reason companies bring Lornets in. For fundraising, Lornets looks at the same underlying system through the questions investors are likely to ask and the evidence needed to answer them.
Typical engagement: £5,000 to £10,000
A technical position you can act on.
Management receives evidence it can use independently: what is exposed, what it means commercially and what should change first. Findings are delivered as a Production Assurance Dossier, with material conclusions reviewed internally before delivery.
Production Readiness Assessment: from £5,000, typically 7 to 10 business days from evidence availability
Production Assurance Position
- Readiness Position
- Ready, Conditionally Ready or Not Demonstrated Ready for the defined scope and operating context.
- Assurance Confidence
- How strongly the available evidence supports the position.
- Critical Readiness Gates
- Conditions materially constraining the next stage, which stronger performance elsewhere cannot offset.
- Engineering Decision
- Keep, refactor or replace, where a decision is warranted by the evidence.
Lornets does not publish a composite numerical score. The position is a judgement supported by evidence, and it is not a certification or guarantee.
A finding is not closed because code changed. It is closed when the evidence changes.
Evidence
- Executive assessment
- System architecture map
- Prioritised risk register
- Readiness Position and Assurance Confidence
Findings
- Security findings
- Reliability and scalability risks
- Data and privacy findings
- Observability and DevOps gaps
Decisions
- Keep, refactor or replace recommendation
- Enterprise readiness gaps
- Prioritised engineering roadmap
- Indicative remediation scope
The Lornets Production Assurance Framework
What we examine
Fundraising readiness, production readiness, enterprise readiness and remediation all run against the same domains. Assessment depth and relative importance vary according to what the system in front of us actually has to withstand.
Core engineering domains
- 01Architecture & Maintainability
- 02Security & Access Control
- 03Reliability & Recoverability
- 04Performance & Scalability
- 05Data & Privacy Engineering
- 06Delivery & Change Control
- 07Observability & Operations
The core domains normally apply to every assessment. Depth varies with what the system actually has to withstand.
Contextual overlays
- Enterprise Assurance
- AI Assurance
- Product / Operational Instrumentation
Overlays activate only where the operating context makes them relevant. They are not equivalent to the core engineering domains.
The answer is not automatically a rewrite.
A weak technical decision can be leaving a material constraint untouched. It can also be replacing a system that did not need replacing.
Lornets establishes the constraint and required operating state first, then chooses the least disruptive response that can meet it. That may mean no change, targeted hardening or refactoring, a hybrid transition or migration.
Forward Deployed AI Engineering
Put AI to work in real operations.
Lornets takes defined AI use cases into production: agents, workflow automation, AI-enabled product capabilities, decision support and operational AI workflows.
The model is not the production system.
A model that works in a notebook is not a capability the organisation can depend on. Lornets also engineers the surrounding production system so the use case can carry real operational weight.
What we take into production
- Agents
- Workflow automation
- AI-enabled product capabilities
- Decision support
- Operational AI workflows
The production system around it
- Integrations
- Permissions
- Evaluation
- Observability
- Operational controls
- Failure handling
- Handover
Why this approach
Our Research & Evidence library reviews primary research, recognised engineering standards and government guidance relevant to rapidly built software, production reliability, AI assurance, enterprise scrutiny and architecture transition.
- Rapid creation and demonstrated production suitability are different questions.
- Production failures extend beyond source code.
- Architecture changes the risk surface rather than simply removing it.
Senior technical judgement stays close to the work.
Dr Anas Almharat is the Founder and Technical Director of Lornets, with more than 15 years of experience across engineering, software, AI and consulting. His career includes taking AI systems from prototype into highly regulated production environments, leading multidisciplinary technical teams and working on large-scale systems supporting critical operations.
His broader experience spans banking and financial services, defence, aerospace, health, energy and technology, across large organisations, startups and consulting environments.
Lornets technical capability
- Software architecture
- Application and platform security
- Reliability and operations
- Scalability and performance
- AI systems assurance
- Enterprise technology delivery
Questions we are asked
Fuller answers sit on the framework and service pages.
What does your product need to withstand next?
If your software is approaching fundraising, greater scale, enterprise customers or increased operational importance, we can establish whether the current foundation is ready.
Lornets, London, United Kingdom. See when to call us