Automate the work between the work
We design AI-powered workflows that understand information, make bounded decisions, connect your systems and route exceptions to humans. Work that used to wait for a click, a copy-paste or an approval now runs itself, with guardrails.
- Reference
- DEMO-014
- Purchase order
- Included
- Receive documentExample workflow step
- Extract & validateExample workflow step
- Check approvalDefined rules and permissions
- Prepare system updateNo external system connected
Rules connect the steps. AI can help extract information.
Start with a handoff everyone recognises.
Between every pair of systems in your company sits work nobody was hired to do: re-keying invoices, chasing approvals, updating the CRM after the call, assembling the report from four tabs. AI automation is the engineering discipline that removes that work. It connects intelligence, business rules, data, applications and human approvals into workflows that actually execute, not chatbots that talk about executing.
What the work includes
We connect AI to the systems you already run. Your CRM, ERP, email, documents, spreadsheets and internal tools stay exactly where they are; the automation layer reads and writes through their APIs, makes the decisions you have bounded it to make, and hands the exceptions to a human with full context. Sales, marketing, support, finance, operations, HR, onboarding, reporting: the processes cross departments, so the automation does too.
Connect the workflows that need it.
Explore the kinds of work this practice covers. Every project starts with its own requirements and review criteria.
Document processing
Invoices, contracts, KYC and claims read, validated and posted into your systems, exceptions routed for review.
Sales & CRM workflows
Enrichment, follow-ups, pipeline updates and handoffs executed from real signals, not reminders.
Finance & reporting
Reconciliation, month-end packs and recurring reports assembled from source systems, checked and delivered.
Onboarding & offboarding
Customers or employees moved through every system, account, notification and approval in one tracked flow.
Back-office operations
Data entry, catalog updates, order processing and internal approvals, the quiet work, automated.
Integration fabric
API-driven connections between your existing tools, so automation reads and writes where the work already lives.
How rules, AI and custom engineering fit together
Rules handle predictable steps. AI can assist with extraction, classification, drafting and retrieval. No-code platforms can connect straightforward workflows; custom APIs or software can cover the parts those tools cannot. We assess the process, define its exceptions, connect the systems, test, add governance, monitor and improve.
Useful intelligence needs clear boundaries.
The model is only one part of the system. Explore the information, permissions and review paths around it.
Relevant information
Select useful sources, respect access and make the supporting context available. Missing or stale information should be visible, not silently filled in.
Bounded actions
Specify what the system may read, prepare or change. Sensitive actions need the right permission and, where appropriate, a person's approval.
Evaluation & fallback
Test routine questions, incomplete inputs and difficult cases. Define when to ask, stop, retry or hand off rather than assuming every answer is correct.
An operating plan
Agree who reviews usage, handles incidents and maintains prompts, data or integrations. Monitoring, cost controls and review records depend on the deployment.
AI is not always the answer.
Clear rules may be simpler. Thin information may need attention first. For sensitive decisions, AI can prepare context while a qualified person decides.
Explore AI strategyA clear path from idea to operation.
Start with a focused scope. Make the information, evaluation and operating responsibilities part of the work.
Map
The process walked end to end, every system, handoff and wait state documented with the people who run it.
Bound
Decisions the machine may make defined explicitly, with thresholds, confidence gates and the human approval points.
Connect
The workflow wired into your existing systems through their APIs. Nothing gets replaced, everything gets connected.
Run
Live with full audit trails, monitoring on every step, and a tuning cadence that widens automation as trust earns.
Illustrative delivery stages. Scope and timing are agreed for your project.
The tools follow the task.
Models, platforms and frameworks are selected around your information, team and operating requirements.
- Workflow engines
- LLMs
- Document AI
- RAG
- CRM & ERP connectors
- Human-in-the-loop
- Audit trails
Find the right kind of AI work.
An agent, a connected workflow, a product feature or a data model. The starting point depends on the problem.
A few things worth asking.
Practical answers about scope, information and what happens after the first build.
No. The automation layer connects through the APIs of the tools you already run, your CRM, ERP, mail, documents and internal apps. We integrate what works instead of demanding a migration.
It stops and asks. Every decision has explicit bounds and confidence thresholds; anything outside them routes to a human with the full context attached. The machine handles the routine, people handle judgment.
High volume, rule-shaped and currently eating someone's week: document intake, follow-ups, reconciliation, onboarding. We map your workflows and sequence by value delivered against effort, quick wins fund the deeper builds.
Every step is logged: what was read, what was decided, on what basis, who approved what. Access follows your existing permissions, data stays in your infrastructure, and the trail answers any auditor's question.
AI project questions
Start with the work you want to change.
Tell us the task, the systems involved and where your team needs help. We’ll work out whether AI, automation or a simpler approach fits.