Services
Six services for enterprise AI and engineering delivery.
From responsible adoption to hands-on delivery, Libra helps enterprise teams turn AI and software priorities into systems that work in production.
Enablement
AI adoption
Move teams from scattered experimentation to practical, governed use. We help prioritise use cases, shape operating guardrails, enable teams and design adoption around real workflows.
The problem
Teams are experimenting in isolation. Nobody can say which use cases matter, which are permitted, or what has to be true before one reaches real work.
What Libra does
- Prioritise candidate use cases against operating value, data sensitivity and delivery effort.
- Shape operating guardrails with security, privacy and data owners.
- Design adoption around the workflows people actually run.
- Enable teams with the patterns, reviews and support they need to keep going.
Designed outcome
A usable AI adoption plan — not another innovation deck.
Suitable engagement model
Advisory and enablement
Secure adoption
Enterprise AI security
Design the controls, threat model, data boundaries and operating policies needed to adopt AI without creating blind spots. Watch Dog is one in-development DLP monitoring product within this broader service.
The problem
AI adoption creates new data flows, model risks and access paths. Security teams need a practical control architecture—not a blanket ban and not an ungoverned rollout.
What Libra does
- Map AI data flows, trust boundaries and threat scenarios.
- Define access, data-handling and model-use controls with security and privacy owners.
- Design evaluation, monitoring and incident-response requirements.
- Integrate controls with the organisation's identity, DLP, logging and governance environment where scoped.
- Explore Watch Dog only as a separate in-development product/design partnership.
Designed outcome
AI use that security, privacy and engineering teams can govern together.
Suitable engagement model
Security advisory or project delivery. Watch Dog design partnerships are handled separately.
ROI
Prototype to production
Turn promising prototypes into reliable software with architecture, evaluation, security review, deployment, observability and ownership designed in.
The problem
Something proved useful in a demonstration and then stalled. The gap is architecture, evaluation, security review and operational ownership — not model choice.
What Libra does
- Agree the architecture, controls and release path with the teams who will run it.
- Build an evaluation set and quality thresholds before the design hardens.
- Deliver deployment, observability, runbooks and a rollback path.
- Confirm acceptance criteria and who owns the system afterwards.
Designed outcome
Production systems that survive contact with the enterprise.
Suitable engagement model
Project delivery
Scaling enterprise AI
Enterprise integrations
Connect AI to the systems where work actually happens: identity, data platforms, service management, ERP, collaboration tools and internal APIs.
The problem
The capability works in isolation, but the systems it must reach have their own owners, contracts, release cycles and failure behaviour.
What Libra does
- Agree interface contracts and data contracts with each system owner.
- Design identity, permissions and least-privilege access across the flow.
- Implement retries, idempotency, timeouts, reconciliation and degraded modes.
- Test against real or contract-faithful endpoints, including failure modes.
Designed outcome
AI that can complete useful work — not another disconnected chat interface.
Suitable engagement model
Project delivery
Modernisation
Legacy apps, plugins and workflows
Rebuild ageing ServiceNow, SAP, Atlassian and ERP extensions on supported APIs and modern frameworks. Simplify brittle workflows, reduce maintenance drag and prepare systems for AI-enabled operations.
The problem
Extensions and workflows the business depends on sit on unsupported APIs, undocumented customisations or manual steps, and every change costs more than the last.
What Libra does
- Recover the real behaviour and dependencies of what exists today.
- Decide what to keep, rebuild on supported APIs, or retire.
- Deliver the replacement in staged, reversible increments.
- Improve operability: logging, monitoring, configuration and support paths.
Designed outcome
Less legacy friction and a platform your team can keep evolving.
Suitable engagement model
Project delivery or managed delivery squad
Engineering capacity
Embedded engineering and delivery squads
Add experienced engineers around a critical initiative or bring in a focused delivery squad. Libra can work inside your team or own a defined delivery stream to reduce the backlog, unblock priorities and expedite delivery.
The problem
Priorities are agreed and funded, but there are not enough senior engineers to move them, and hiring will take longer than the work can wait.
What Libra does
- Add senior contributors into your team, standards and review process (staff augmentation).
- Or take a defined delivery stream with agreed scope and acceptance criteria.
- Report progress against those criteria, including when something is slipping.
- Leave documentation, tests and runbooks behind, not just commits.
Designed outcome
More delivery capacity without waiting for a long hiring cycle.
Suitable engagement model
Embedded engineering or managed delivery squad
How to engage Libra
Start with the constraint, not a generic package.
The right engagement depends on whether you need a decision, a delivered outcome or more engineering capacity.
You need clarity
Advisory sprint
Prioritise the use case, surface the risks and leave with a practical decision, control set or delivery roadmap.
You need a result
Delivery engagement
Give Libra a defined production, integration or modernisation outcome with agreed acceptance criteria and one accountable delivery lead.
You need capacity
Embedded engineers or a delivery squad
Add senior contributors inside your team or assign Libra a focused delivery stream to reduce backlog and expedite delivery.
What ownership means
When we say we own the problem, we mean one accountable delivery lead, documented decisions, working code, tests, runbooks, agreed acceptance criteria and a clear transition or support window. Ongoing managed support is included only when it is part of the engagement.
Engineering across the platforms your enterprise already runs.
Libra designs and delivers across cloud, model, security, data, developer and enterprise application ecosystems.
Cloud and AI
- AWSCloud architecture, IAM, data and AI service integration, deployment and observability.
- Microsoft AzureCloud architecture, IAM, data and AI service integration, deployment and observability.
- Google CloudCloud architecture, IAM, data and AI service integration, deployment and observability.
- OpenAIModel integration, evaluations, guardrails, retrieval and agent workflows.
- AnthropicModel integration, evaluations, guardrails, retrieval and agent workflows.
Security, edge and data
- CloudflareEdge, network and application-security integration.
- CrowdStrikeSecurity operations and endpoint-security integration.
- ZscalerZero-trust and secure-access integration.
- SnowflakeEnterprise data, analytics and AI data workflows.
- DatabricksData engineering, lakehouse and ML/AI workflows.
Engineering and enterprise
- GitHubModern developer workflows, CI/CD, code security and platform integrations.
- ServiceNowCustom apps, workflows, integrations and legacy plugin modernisation.
- SAPInterfaces, extensions, process automation and upgrade-safe integration patterns.
- AtlassianJira and Confluence workflows, apps, automations and integrations.
- SupabaseApplication backends, Postgres, auth and storage.
- VercelModern web application delivery and deployment.
Technology names and marks belong to their respective owners. Their inclusion describes relevant engineering ecosystems and does not imply partnership, certification or endorsement.
Start at stage one.
Frame the operating outcome and the evidence that would prove it. Everything else follows from that.