AI Workflow Automation that ships, audits, and operates.
We move document-heavy, approval-heavy, and case-heavy workflows from manual or RPA into production AI systems. For BFSI, healthcare, and public sector enterprises whose operations scale with headcount because nothing else has worked.
AI workflow automation replaces repetitive document-heavy or case-heavy work with governed AI systems that ingest information, extract fields, recommend next actions, route exceptions, and preserve human accountability through review gates and audit logs. The AI is one component. The system around it, intake, extraction, decisioning, human review, integration, audit, and operation, is what makes it hold up in a regulated environment.
The workflow is the product, not the AI.
Ranges before you spend a meeting on us.
Use Case Discovery
Production Build
RPA-to-AI Modernization
Typical first-year program investment $320K–$460K. Typical payback 9 to 14 months. Exact figures are named on the scoping call and written into the SOW.
Three situations, three engagement paths.
You're moving a manual workflow into AI for the first time.
A workflow your team handles manually (claims review, contract analysis, case triage, document classification) has scaled past headcount.
Your RPA estate has plateaued.
Bots break on document variations, and exceptions consume the time the bots were meant to save.
You have an AI workflow in production that's not holding up.
Accuracy below target, exception rate higher than the manual baseline, and compliance can't defend decisions.
From inventory to hypercare.
AI Use Case Discovery
Weeks 1–3: workflow inventory and ROI ranking, top 3–5 shortlisted. Weeks 4–6: current-state process mapping, target-state architecture, build-vs-buy. Weeks 7–8: business case with payback model and the SOW for the build.
Production Build
Weeks 9–11: foundation (ingestion, extraction, chunking) with a demo on synthetic data. Weeks 12–16: decision logic, human-in-the-loop, exception handling, accuracy testing. Weeks 17–20: audit trail, decision logging, compliance reporting, integration. Week 21: production cutover with a pilot group. Week 22: handover.
Hypercare and Handover
Senior engineers on call, daily monitoring, and the operations runbook finalized against the live system.
AI Optimization & Governance Retainer
Monthly performance review, drift monitoring, new workflow onboarding at roughly one per quarter, and compliance and audit support.
Who does the work.
How we build it.
The workflow is the product, not the AI
Intake, decisioning, review, integration, and audit are scoped as one system.
Human-in-the-loop is a feature, not a fallback
Review gates preserve accountability where the stakes demand it.
Audit trail is built in, not retrofitted
Every decision is logged with input, model output, confidence score, and reasoning chain.
Framework alignment ships with the system
NIST AI RMF, ISO 42001, EU AI Act, plus HIPAA, DORA, and SEBI where they apply.
Cloud-agnostic by architectural decision, not by inheritance.
Model providers
Document AI / orchestration
Deployment / integration
Where this workflow discipline lands.
BFSI
Claims review, loan document triage, AML case summarization, policy gap extraction; confidence-gated routing plus a logged decision trail.
Healthcare
Prior authorization support, payer operations, clinical document routing, claims exception review; HIPAA and residency scoped.
Public Sector
Beneficiary document review, licensing applications, citizen request triage, credential verification; transparency under public scrutiny.
Only where you decide it should. We tune confidence thresholds so safe cases run unattended and the rest route to a person.
AI workflows that ship, audit, and operate in regulated environments.
Bring the workflow that is scaling with headcount. A senior practitioner will name the shape and a rough range.