AI & AUTOMATION
Apply AI and automation where they genuinely improve the work.
We help organisations automate repetitive processes, build AI-enabled applications and explore intelligent workflows with human accountability and practical governance.
AI is a tool, not the objective.
Akinary starts with the business or process problem and evaluates whether conventional automation, software, AI or a combination is appropriate. Not every workflow needs a language model.
Typical scenarios
Repetitive manual work is slowing a team down
Staff spend hours on repetitive data entry, document handling or approvals that could be automated.
Documents and unstructured content are hard to process
Information arrives as PDFs, emails or scanned documents and needs to be classified, extracted or summarised.
A workflow could benefit from an AI assistant
Staff or customers need faster access to information through a conversational or search interface.
AI is being considered without a clear use case
There's appetite to use AI, but it isn't yet clear where it would create measurable value.
Good candidates for automation
High volume
The same kind of work arrives often enough to matter.
Repeatable
Most cases follow a recognisable pattern.
Identifiable inputs
The information needed arrives in forms, documents, emails or systems that can be read.
Clear rules or decision boundaries
It is possible to say what a correct outcome looks like.
A clear review or escalation point
Someone can check exceptions and uncertain cases.
EXAMPLE APPLICATIONS
What AI and automation can do in practice
Six common workflows, what automation or AI can take on, and where people stay in control.
Illustrative examples of the kinds of work we can help automate — not case studies.
Document and invoice processing
Today
Invoices, forms and PDFs arrive by email and are re-keyed by hand.
Automation or AI
Extract and classify the key fields, then pass them to the right system.
People stay in control
Staff confirm unusual or low-confidence items before they are posted.
Approvals routing
Today
Requests sit in inboxes while someone works out who should approve them.
Automation or AI
Route each request to the right approver under defined rules, with its context attached.
People stay in control
Approvers still make the decision; exceptions are escalated.
Service-request triage
Today
Incoming requests land in a shared queue and are sorted manually.
Automation or AI
Classify, prioritise and route requests, and draft a first response where appropriate.
People stay in control
Staff review drafts before anything sensitive is sent.
Internal knowledge search
Today
Answers are spread across documents, policies and past requests.
Automation or AI
A search or conversational interface that finds relevant material and shows its source.
People stay in control
Answers point back to their sources so staff can verify them.
CRM and record updates
Today
Details from emails, calls and forms are copied into CRM or case records by hand.
Automation or AI
Draft record updates from incoming information and flag what has changed.
People stay in control
Staff approve updates wherever accuracy matters.
Reporting and system-to-system automation
Today
Reports are assembled by exporting and combining data from several systems.
Automation or AI
Scheduled data flows between systems and automatically prepared reports.
People stay in control
Owners review figures and definitions before reports are relied on.
Where automation is a good fit, the benefits are practical: less re-keying, fewer manual hand-offs, faster routing, more consistent handling and more staff time for work that needs judgement.
Where AI fits in the workflow.
A simplified view of how AI and automation typically sit inside a workflow, with human review kept in the loop.
Repetitive, manual workflow
Documents, emails, forms, requests
AI-assisted automation
Extract, classify, route, draft
Confidence & validation check
confident, within rules
Automated completion
uncertain or high-risk
Human review & escalation
Accountable, useful outcome
Traceable where practical
Responsible delivery
Human accountability
Material decisions and client commitments remain subject to human oversight.
Appropriate data handling
AI architecture reflects the sensitivity and governance requirements of the information being processed.
Evaluate performance
AI systems are tested against defined tasks and expected outcomes rather than judged only by demonstrations.
Control automation
Where AI is uncertain or high-risk, we design escalation and human review.
Private deployment where appropriate
Architectures may use customer-controlled or private deployment models where project requirements call for them.
How we approach AI & automation
We start with the workflow or decision that needs improving, prototype quickly to test technical and practical feasibility, and build only what's proven to work — with human review built in wherever the automation is uncertain or high-risk.
Understand
The workflow or decision to improve
Design
Choose automation, software, AI or a mix
Prototype
Test technical and practical feasibility
Build
Build only what's proven to work
Test
Against defined tasks and outcomes
Improve
Refine, with human review where uncertain or high-risk
Understand
The workflow or decision to improve
Design
Choose automation, software, AI or a mix
Prototype
Test technical and practical feasibility
Build
Build only what's proven to work
Test
Against defined tasks and outcomes
Improve
Refine, with human review where uncertain or high-risk
Related capabilities
Suitable for
- Businesses & Enterprise
- Non-Profits & Purpose-Led Organisations
- Government & Public Sector