Automation that survives the audit, the upgrade, and the people who built it
Most RPA programmes plateau at twenty bots and a graveyard of broken ones. We treat automation as software engineering — versioned code, instrumented telemetry, regression tests, and a CoE operating model that scales past the early wins. The result is a portfolio that compounds rather than decays, and a finance team that can defend the savings number to the auditor.
What we deliver
Process library
Two hundred pre-mapped processes across finance, HR, IT, supply chain, contact-centre, and regulatory ops. Each one ships with a process definition document, an automation feasibility score, expected effort range, and the reusable components we built last time. Discovery becomes selection, not invention.
Intelligent automation
RPA on its own only addresses structured, deterministic work. We compose bots with DocuMage for document understanding, ChatNext for conversational triggers, and bespoke ML for classification and exception handling. The combination is what unlocks the seventy percent of back-office work that legacy RPA cannot touch.
Platform-neutral delivery
Certified across UiPath, Automation Anywhere, Blue Prism, Power Automate, and increasingly the open-source stack. We will pick the right platform for your IT landscape and existing licences — and have rescued enough failed implementations to be honest about the trade-offs before contracts are signed.
Engineering discipline
Source control on every workflow, code review on every PR, unit tests on every reusable component, environment-promotion pipelines, and immutable deployment artefacts. Your bots behave like production software because they are production software — not Excel macros written by a consultant who left in month nine.
Full-coverage operations
A twenty-four-seven NOC monitors every bot, with SLA-backed response, automatic exception recovery for known failure modes, and on-call escalation for novel ones. Mean time to detect is under five minutes. Mean time to recovery is benchmarked monthly and trends down quarter on quarter.
Benefits realisation
Every bot ships with an instrumented baseline, a target FTE-equivalent saving, and a monthly realisation report your CFO can defend. We make the value visible so the programme keeps funding itself — and we walk away from automations where the value case does not survive scrutiny.
RPA bot in action
How a query actually flows.
A real trace through the sovereign stack. Six stages, ~1.4 seconds end-to-end, zero packets leaving your perimeter.
How we deliver
Opportunity assessment
We combine task-mining tools, application logs, and structured interviews with process owners to identify and score automation candidates by complexity, volume, and benefit. You receive a ranked backlog, an investment profile, and a recommendation on platform fit before the first bot is built.
Solution design and build
Each automation goes through a formal solution design — process map, exception matrix, security review, and reusable-component reuse plan — before development. Build, peer review, and UAT typically run four to eight weeks per process, faster if it draws heavily on the library.
Deploy and stabilise
Controlled cutover with a documented rollback path, followed by four weeks of hypercare in which a senior engineer is on call and instrumentation is tuned. The bot enters steady-state operations only when it has hit its KPIs for two consecutive weeks.
Scale the portfolio
Sprint cadence delivers a new wave of automations every six to eight weeks. We track portfolio health metrics — uptime, exception rate, business hours saved — and retire automations that fall below the value threshold instead of letting them rot.
Mature the CoE
We help you build the operating model: governance, demand intake, citizen-developer enablement, platform standards, and benefits reporting. The end state is a CoE that runs without us, with MindMap as a partner for surge capacity and specialist work.
RPA & Automation across every sector
The stack we build on
RPA platforms
ERP & finance systems
HR & people systems
Intelligent automation
Process mining
DevOps and ops
"We had thirty bots running and nineteen of them broken when MindMap took over. Six months later we had eighty-one bots, ninety-nine point eight percent uptime, and a portfolio dashboard the audit committee actually trusts."— Group VP, Shared Services, Listed Global BPO
How we work together
Common questions
Which RPA platform should we standardise on?+
It depends on your existing licence estate, your IT operating model, and your tolerance for vendor lock-in. UiPath remains the safest enterprise default with the deepest ecosystem; Power Automate is the right answer if you are deep in Microsoft and want citizen-developer reach; Automation Anywhere and Blue Prism each have specific strengths in regulated environments. We are certified on all four and platform-neutral in advice — if you already own licences, that usually settles the question.
Why do RPA programmes stall after the first twenty bots?+
Because the first wave is built as projects and the next wave needs to be built as a portfolio. The failure modes are predictable: no reusable components library so every bot is bespoke, no production-grade DevOps so bot changes go through change tickets, no exception-handling discipline so the NOC drowns in noise, and no benefits-realisation engine so finance loses faith. The remedy is engineering discipline applied from day one — which is harder to retrofit than to start with.
What happens when an underlying application changes and breaks the bot?+
Two answers. First, we minimise the blast radius by using API-first integration wherever the application supports it and only falling back to UI automation where it does not. Second, when UI changes do break a bot, our NOC detects it within five minutes, an automated rollback runs while an engineer is paged, and the typical resolution is under four business hours. Application teams that warn us in advance of changes get zero downtime.
Can RPA handle unstructured data like PDFs, emails, and voice?+
Pure RPA cannot — and pretending otherwise is how bad implementations are built. We combine RPA with DocuMage for documents, ChatNext for conversation, and custom ML for classification. This intelligent-automation stack handles the seventy percent of back-office work that is unstructured. We will not sign a statement of work that depends on rules-only RPA for unstructured input.
How do you measure and defend the savings?+
Before any bot ships, we instrument the baseline: cycle time per transaction, error rate, FTE allocation. After go-live the same instrumentation runs in production and reports monthly. We work with your finance team to set the labour-rate assumption and reinvestment policy. The output is a benefits realisation pack your CFO can take to the audit committee — not a PowerPoint with directional arrows.
What does ongoing support look like?+
Twenty-four-seven NOC with SLA-backed response, weekly portfolio health reports, quarterly business reviews, and a change pipeline that lets you request enhancements and additions without renegotiating the master agreement. Most clients also engage us for an annual deep-dive on which automations to retire, replatform, or expand.
Ready to explore RPA & Automation?
Speak to our engineering team. No sales pitch — just a technical conversation.
Start a conversation →