Most enterprise workflows are a mix. Some steps are rule-bound and deterministic — AA excels there. Other steps need interpretation, judgment, or synthesis — agents excel there. We don't force one tool to do both jobs.
Forms, data entry, system-to-system transfers, scheduled reports, rule-driven approvals, clicks across legacy UIs.
Document interpretation, unstructured data extraction, exception handling, summarization, judgment calls — the steps a rule-based bot can't confidently complete.
Start with structured. Add agents where rules break. Deploy together as one workflow.
Not every engagement uses Automation Anywhere. When it does, here's how.
Classical RPA
Rule-based bots automating repetitive tasks — reconciliations, form filling, report distribution, system-to-system transfers. AA Bot Runner + Control Room, deployed on your infrastructure.
AA's agentic layer
AA's native agent framework — we design the reasoning steps, integrate local LLMs or frontier-model APIs, and wire them into existing bots so structured automations can now handle exceptions and judgment calls.
Intelligent extraction
Document Automation (formerly IQ Bot) for invoices, contracts, claims, statements. LLM-assisted extraction for fields rules can't reliably parse. Human-in-the-loop review where confidence is low.
Frontier reasoning inside bots
We integrate frontier LLMs into AI Agent Studio, so existing AA bots can call out for the reasoning-heavy steps: complex email classification, exception escalation drafting, policy interpretation, multilingual customer response.
From first workflow audit to a mature Center of Excellence running hundreds of bots.
Process discovery workshops, top-10 automation candidates ranked by ROI, AA vs agent vs API recommendation per candidate, one working proof-of-concept bot on your real data.
Fixed-fee · Deliverable: report + roadmap + working bot
Three production-grade bots across one business function. Control Room setup, Bot Runner deployment, credential vault, monitoring dashboards, 60 days hypercare.
Fixed-fee per bot · Deliverable: deployed bots + runbooks
For customers with existing AA deployments. AI Agent Studio configuration, frontier-LLM reasoning steps, governance policies, three reference bots migrated from rule-only to LLM-enhanced workflows.
Fixed-fee · Deliverable: migrated workflows + playbook
Bot health monitoring, exception triage, schedule optimization, version upgrades, UI-drift remediation, quarterly bot review. Three tiers by bot volume.
Monthly subscription · Deliverable: uptime report + office hours
For organizations ready to scale automation across functions — we design the governance model, build the intake pipeline, train your internal developers on AA + agents, and hand over a running factory that produces bots predictably.
Engagement-scoped · Deliverable: CoE framework + trained team + first 10 bots
We don't push a single tool. The Automation Assessment figures out the right mix for your workflows — and sometimes the answer is “an API, not a bot.”
Decision Stack is prescriptive — agents reason and decide; engines optimize and enforce; bots execute. AA's APA suite is the execution layer: it's what actually does the work after the decision is made.
RPA bots execute structured steps. AI Agent Studio handles the reasoned ones. Document Automation reads the unstructured inputs. Process Discovery surfaces what to automate next. One execution layer that takes prescriptive decisions and turns them into action — auditable, governed, and 24/7.
Document Automation extracts unstructured content into governed knowledge sources — feeding RAG and search.
Bot telemetry and Process Discovery output become inputs for predictive models — what fails, what bottlenecks, what to forecast.
We work with multiple RPA platforms. We recommend Automation Anywhere when the engagement calls for cloud-native deployment, an open API surface (so bots can be wired to modern agent frameworks and frontier-LLM APIs), and AI Agent Studio as a first-class citizen rather than a bolt-on. Where the match is wrong — different platform, different constraints — we say so and recommend a better fit.
