Automation
Rules, exceptions and outcomes are clear and repeatable enough to execute deterministically.
AI & AUTOMATION
AI and automation for processes that can genuinely work smarter.
Some processes are best improved with deterministic automation, others benefit from AI, and only a smaller subset requires agents. Link2Leap helps determine the right approach and integrate it into the systems and workflows that already matter.
When AI & Automation becomes relevant
When valuable work gets stuck between people and systems
The starting point is a process that involves unnecessary manual work, handovers or recurring judgement, not a desire to use a particular AI tool.
- 01
People repeatedly collect, interpret and transfer information between systems.
- 02
Knowledge work contains recurring judgement steps that consume significant time.
- 03
A process has many handovers, manual checks or repetitive decisions.
- 04
Existing systems contain the required data and actions, but the workflow between them remains manual or fragmented.
What we do
Fit the technology to the process
We connect interpretation, decision-making and system actions where they add value, with explicit boundaries around what is and is not automated.
01
AI Integration
Embed AI capabilities into existing software and processes where interpretation, classification, extraction, generation or decision support adds value.
Explore AI Integration02Agentic AI
Design controlled multi-step workflows that gather information, reason within defined boundaries and trigger actions across systems, with appropriate guardrails and human oversight.
Explore Agentic AI03Workflow Automation
Automate repeatable process steps and system interactions with deterministic logic where AI is unnecessary.
Explore Workflow AutomationAI, automation or agent?
Choose the simplest reliable solution that fits the process
The required technology follows from the nature of the work. Hybrid solutions are common when fixed rules, interpretation and dynamic coordination meet within one process.
- Not every process needs AI. Not every AI application needs an agent.
AI
Interpretation or language and context understanding is needed to process information or support a human decision.
Agent
Multiple steps, systems and decisions need dynamic coordination within explicit permissions and boundaries.
Our approach
From process question to controlled operation
We start with the work as it happens today, its exceptions and the intended outcome. We then design and integrate only what genuinely contributes.
- 01
Understand the process
We map the workflow, decisions, exceptions, systems, data and bottlenecks.
- 02
Choose the approach
We determine where deterministic automation, AI, an agent or a combination fits.
- 03
Integrate
We connect the solution to existing applications, APIs, data and permissions.
- 04
Control & improve
We establish validation, monitoring, human oversight and controlled iteration where risk and use require them.
Technical depth
What reliable process automation requires technically
A solution works in practice only when process logic, data, integrations and control are designed as one system.
- Process logic & orchestration
- Organise steps, states, exceptions and recovery paths explicitly.
- Data & context
- Determine which information is necessary, usable and permitted at each step.
- Integrations & APIs
- Allow existing systems to read, write and perform actions safely.
- Guardrails & permissions
- Enforce permissions, boundaries and allowed actions technically.
- Human-in-the-loop
- Place human review, approval or escalation where consequences require it.
- Monitoring & observability
- Make behaviour, quality, errors and exceptions visible and traceable.
When we are not the right fit
AI is not an end in itself
Our contribution fits when a concrete process can improve and the chosen technology must work reliably within existing operations. We are usually not the best fit when:
- The primary goal is simply to ‘do something with AI’.
- A straightforward rule-based automation already solves the problem adequately.
- There is no stable process, usable data or system access to integrate with.
- The organisation wants unsupervised autonomy in a high-impact workflow without appropriate controls.
A process where you want to know whether AI genuinely adds value?
Tell us about the workflow, the systems involved and the bottleneck. We can determine whether automation, AI, an agent or a combination is the sensible route.
Discuss where automation can help