
Your employees spend a large portion of their time on repetitive, rule-based computer tasks: copying data between systems, filling forms, generating reports, processing emails, and updating spreadsheets. RPA (Robotic Process Automation) creates software robots that perform these tasks 80% faster, 24/7, with zero errors. The RPA market reached $3.2 billion in 2025 with average ROI of 300%. Companies deploying RPA recover 20,000+ hours annually per department and redirect human talent to work that requires judgment and creativity.
An accounts payable clerk enters 200 invoices per week from emails into the ERP — 15 minutes each, 50 hours per week of data entry. An HR coordinator copies new hire information from applications into 5 different systems. A financial analyst pulls data from 3 databases into Excel every Monday morning to create a weekly report.
These tasks are repetitive, rule-based, and error-prone when done manually. They require no judgment — just clicking, typing, copying, and pasting in the same sequence every time. But they consume hours of skilled employee time that could be spent on analysis, problem-solving, and customer relationships.
The cost isn't just salary — it's opportunity cost. Every hour spent on data entry is an hour not spent on work that moves the business forward.

We build RPA bots that replicate human interactions with computer systems.
Attended bots work alongside employees, automating parts of their workflow. An agent clicks a button and the bot pulls customer data from 3 systems into a single view. The bot handles the repetitive lookup; the agent handles the conversation.
Unattended bots run independently on schedules or triggers. An invoice arrives in email → bot extracts data → validates against PO → enters into ERP → sends confirmation. No human involvement for routine cases.
AI-enhanced RPA combines traditional RPA with machine learning for tasks that require understanding: reading unstructured documents, classifying emails, extracting data from varied formats, and making simple decisions based on patterns.
Orchestration manages multiple bots working together, handling exceptions, retrying failures, and routing edge cases to human workers. Dashboards show bot activity, completion rates, and error rates in real-time.
Every bot is built with error handling, logging, and alerting — when something unexpected happens, the right person is notified immediately.
We identify and evaluate candidate processes for automation based on volume, frequency, rule-based nature, and ROI potential. We document the current process step-by-step.
We design the automation workflow: which steps to automate, exception handling rules, human-in-the-loop touchpoints, and integration with existing systems.
We build the RPA bots, test against real data scenarios including edge cases and error conditions, and validate output accuracy against manual process results.
Bots deploy to production with monitoring dashboards tracking execution count, success rate, processing time, and exceptions. We optimize based on production performance.
No commitments. Tell us what you need and we'll tell you how we'd solve it.
Challenge: AP team manually entered 800 invoices per week from emails and PDFs into NetSuite — 3 full-time employees spent 90% of their time on data entry
Solution: RPA bot monitoring inbox for invoices, extracting data using AI (vendor, amount, line items, dates), matching against POs, and entering into NetSuite. Exceptions queued for human review.
Result: Invoice processing time reduced from 15 minutes to 2 minutes each; 3 AP employees redirected to vendor management and analysis; error rate dropped from 4% to 0.1%
Challenge: New hire onboarding required updating 7 systems (HRIS, payroll, IT provisioning, badge access, email, training, org chart) — taking HR 4 hours per new hire
Solution: RPA bot triggered by HRIS record creation that propagates employee data to all connected systems, creates accounts, and sends welcome emails with credentials
Result: Onboarding time reduced from 4 hours to 15 minutes per hire; zero data entry errors across systems; new employees productive on day 1 instead of day 3
Challenge: Insurance eligibility verification required checking 3 payer portals for each patient visit — front desk staff spent 2 hours daily on verification alone
Solution: RPA bot checking eligibility across all payer portals automatically before appointments, flagging coverage issues for staff review
Result: Eligibility verification time reduced from 2 hours to 10 minutes daily; claim denial rate from eligibility issues dropped 85%; front desk staff refocused on patient experience
Workflow backends run on Next.js 16 with Payload CMS 3 managing automation rules through an admin interface. PostgreSQL handles execution logs, state tracking, and audit trails. When integrations need custom logic beyond what Zapier or Make offer, we build it directly — same codebase, no platform limitations.
We use Claude, GPT-4o, Deepgram, and ElevenLabs in production daily — for coding, content generation, voice automation, and customer interactions. We're not consultants who read about AI; we're practitioners who ship AI systems every week.
Self-hosted infrastructure means your data stays where you control it. No vendor lock-in to SaaS platforms that can change pricing or terms. Full PostgreSQL audit trails, your own backups, and GDPR compliance built into the architecture.
From mapping your current processes through implementation to ongoing optimization — one team handles everything. No handoff between strategy consultants and developers. The person who designs your workflows also builds and maintains them.
Our internal operations run on the same automation patterns we implement for clients: automated deployments, monitoring alerts via Telegram, content generation pipelines, and CRM synchronization. We practice what we preach — every automation recommendation comes from real operational experience.
Any repetitive, rule-based computer task: data entry between systems, copy-paste workflows, report generation from multiple sources, form filling, email processing and routing, invoice data extraction, payroll calculations, compliance checks, file management, and system-to-system data transfer. The ideal RPA candidate is a task performed the same way every time, executed frequently, and involving structured data across 2+ systems.
API integration connects systems programmatically through code — it's the preferred approach when APIs exist. RPA interacts with systems the way a human does — clicking buttons, typing into fields, reading screens. RPA works with legacy systems that don't have APIs, web portals that only have a UI, and third-party systems you can't modify. In practice, the best solutions combine both: APIs where available, RPA where necessary.
A simple bot (single system, linear workflow, 5-10 steps) takes 1-2 weeks. A medium-complexity bot (multi-system, conditional logic, exception handling) takes 2-4 weeks. A complex bot (AI-enhanced document processing, multiple decision points, orchestration with other bots) takes 4-8 weeks. We typically start with a quick win (simple, high-frequency process) that delivers ROI within the first month.
Describe the manual, repetitive computer tasks your team performs daily. We'll assess automation potential and estimate the hours you'd recover.
Free process assessment · 300% ROI · First bot live in 4 weeks
Challenge: Account opening required manual data entry from application forms into core banking, KYC system, and compliance database — 45 minutes per new account
Solution: RPA reading application data, performing automated KYC checks, entering data into all required systems, and generating welcome kits — human review only for flagged applications
Result: Account opening time reduced from 45 minutes to 8 minutes; same-day account activation enabled; compliance data accuracy improved to 99.9%
Fixed-price projects with clear milestones and deliverables. You approve each phase before we proceed to the next. No open-ended hourly billing, no scope creep surprises. Ongoing support is a separate, transparent monthly agreement.
Every bot includes exception handling for known edge cases and a catch-all for unknown exceptions. When something unexpected occurs: the bot logs the error with screenshots, queues the item for human processing, sends an alert to the designated person, and continues processing the remaining items. Nothing gets lost or silently fails. Exception rates typically start at 5-10% and drop below 2% as we refine handling for observed edge cases.