Staff Augmentation

Staff augmentation for AI, automation, finance, and platforms shouldn’t feel like a bolt-on project or a risky science experiment—it should feel like a disciplined, operations-grade capability that unblocks your teams and pays for itself quickly. At AuctaMorph, we design for the messy reality of enterprise environments: legacy systems, shifting priorities, audits, and hard SLAs. Our approach starts with the pains your teams live with every day and works backward to orchestration patterns, guardrails, and adoption plans that stick.

Common pain points we encounter include talent shortages delaying programs • over-reliance on single contractors and key-person risk • slow onboarding due to poor documentation • difficulty flexing capacity during peaks. Individually these issues are frustrating; together they create gridlock that inflates cycle times, buries talented analysts under repetitive work, and starves leadership of timely insight. We treat these not as isolated bugs, but as system design problems—root-causing where time is lost, what creates exception loops, and which steps truly require judgment versus those that can be automated end-to-end.

Beyond RPA, we deploy seasoned Accounts Payable, Accounts Receivable, and broader Finance & Accounting professionals—ready to plug into your Procure-to-Pay, Order-to-Cash, Record-to-Report, and Plan-to-Perform processes. Our pods blend human expertise with automation & AI so you get throughput today while building durable, lower-cost ways of working for tomorrow.

• AP: invoice intake & triage, 2/3-way match, vendor master hygiene, GR/IR cleanup, payment runs, aging/backlog burn-down.
• AR: cash application, deductions & disputes, dunning, credit risk checks, remittance matching.
• F&A: reconciliations, journal entry prep/post, fixed assets & depreciation, intercompany, close acceleration, audit support, FP&A ops.

Typical roles we supply: AP Specialists, AR Analysts, GL Accountants, FP&A Analysts, Payroll & Tax Ops, ERP Specialists (SAP FI/CO, NetSuite, Oracle), RPA Developers (UiPath, Automation Anywhere, Power Automate), and AI Engineers for document processing & agent workflows.

1. Diagnose & benchmark: Map your intake-to-posting flows, quantify error/exception hotspots, and set SLA/KPI baselines.
2. Stabilize & clear backlog: Stand up a staffed AP/AR/F&A pod to normalize inputs, fix master data, and bring queues under control.
3. Automate repeatables: Deploy RPA & IDP for intake, match, validations, postings; add AI agents for document Q&A and exception triage.
4. Human-in-the-loop orchestration: Route only judgment calls to analysts with tight turnarounds; log decisions for continuous learning.
5. Measure & improve: Live dashboards for aging, STP (straight-through processing), accuracy, cycle time, and cost-per-document.

Our pricing is transparent and geared toward time-to-value. Simple processes start at USD 7,000, medium at USD 13,000, and complex at USD 19,000—plus an optional managed run fee starting at USD 300 per bot per month to keep your platform updated, outputs monitored, and issues fixed within SLAs.

We’re comfortable with outcome-linked models where appropriate. The rule of thumb: each bot should pay itself back within one to three months via hours reclaimed, leakage reduced, or revenue accelerated.

Context: A global enterprise faced a compliance risk and vendor escalations with a backlog of 200K invoices awaiting upload across an ERP and a contracts repository. Formats varied (PDF/scan/email), supplier data required cleansing, and multiple approval chains existed.

Hybrid team: We deployed an AP pod (lead + analysts across time zones) alongside an automation squad (RPA + IDP engineers). Humans focused on exceptions and vendor comms; bots handled bulk intake, validation, and posting.

Outcomes (month 1): 90–95% STP on clean POs; remaining exceptions resolved within 24–48 hours; backlog cleared in 28 days; cycle time reduced from ~8 days to ~1–1.5 days; zero duplicate postings; audit-ready logs and variance explainers delivered to Finance.

If you’re starting from zero, we’ll stand up a lean CoE aligned to your governance model. If you already have bots in production, we’ll stabilize what’s running, retire what’s obsolete, and scale what works. Either way, you get momentum you can measure.

Our implementation approach follows an iterate-to-value rhythm. We start with discovery workshops and a baseline of current cycle times, backlog, and error rates. We then select 2–4 high-value use cases to deliver in the first 6–8 weeks, establishing patterns, repositories, and observability from day one.

Every sprint ends with working software, documented runbooks, and stakeholder demos. We measure business impact—not just story points—so sponsors see real movement. Within a quarter, you have a reliable pipeline of automations and a self-serve backlog that business teams help prioritize.

In healthcare revenue cycle, we’ve automated eligibility checks, claims status, and payment posting—launching 60+ bots that free up more than 5,000 staff hours every month.

In finance, we’ve accelerated reconciliations, journal posting, and asset depreciation with guardrails that satisfy audit teams and shorten close cycles.

In supply chain, our automations improve promise dates, ASN capture, and track-and-trace exceptions—limiting expedites and boosting OTIF.