AI/ML
Intelligent automation that handles the variable, unstructured work that rules-based RPA cannot — built on ML models that improve with operational data.
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Years in production
What it is
AI-powered automation uses machine learning and language AI to handle variable, unstructured tasks that conventional rule-based automation cannot process — including document understanding, natural language routing, decision-making under uncertainty, and exception handling.
What you get
Traditional RPA breaks when inputs vary. A rule that works on 80% of invoices fails on the remaining 20% because the layout changed, a field is missing, or the data is in a non-standard format. AI-powered automation adds a reasoning layer that handles variation — classifying, extracting, and routing even when inputs do not conform to a fixed template.
We build automation systems that combine document AI (extracting structured data from PDFs, emails, and forms), decision models (routing, approvals, and exception flagging), and workflow orchestration (triggering downstream systems via API). The result is a pipeline that processes the majority of cases fully automatically and escalates edge cases to humans with context already populated.
Integration is treated as a first-class concern. We connect automation pipelines to your ERP, CRM, document management system, and communication tools — ensuring outputs flow to where decisions are made, not into a separate dashboard nobody monitors.
Key capabilities
Each engagement is scoped to your requirements — these are the core capabilities we bring to the table.
Exception handling with human-in-the-loop escalation
RPA augmentation with AI for unstructured inputs
ERP and CRM integration (SAP, Salesforce, ServiceNow)
Process mining to identify automation candidates
Monitoring dashboards with throughput and accuracy metrics
Our process
A structured, engineering-led approach that moves from understanding your goals to a production system — with no handoff surprises.
Typical engagement
8–16 WEEKS
We map your goals, constraints, and existing infrastructure. Scope is defined and success criteria agreed before any development begins.
We design the technical approach, select the right tools, and produce a milestone-driven delivery plan with no ambiguity.
Iterative development with regular demos. Code reviews, test coverage, and documentation happen in parallel — not at the end.
Production release with monitoring setup and handover documentation. We stay close during the first weeks post-launch.
Built with
RPA automates deterministic, structured tasks — clicking buttons, copying fields, following fixed rules. AI automation handles variable inputs: documents with different layouts, emails with ambiguous intent, images that need interpretation. The two complement each other — AI handles the intake and classification, RPA executes the downstream steps.
It depends on the task and the cost of errors. For low-stakes routing, 90%+ accuracy with human review for low-confidence cases is typically acceptable. For financial data extraction, you may need 99%+ on critical fields with mandatory human verification. We define acceptance criteria with you during scoping.
Yes. We integrate via APIs, webhooks, and database connectors. Most enterprise systems expose integration surfaces — if yours do not, we can add lightweight middleware. Full system replacement is not required.
Work with us
Share what you're building — we'll respond within one business day with questions or a proposal outline.
