Executive overview
Document AI and IDP 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 unstructured PDFs, scans, and handwritten notes that derail STP • manual keying and validation loops across AP, KYC, and onboarding • fragile templates that break with small vendor or form changes • low confidence predictions that force 100% manual review • poor traceability for auditors across versions and corrections. 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.
Pain points we eliminate
Our remedy playbook is pragmatic: multi-model ensembles (vision+OCR+LLM) with confidence-driven routing; pre/post-processors that normalize vendor layouts and edge cases; human-in-the-loop stations that learn from feedback; field-level lineage with audit-ready logs and reprocessing; deployable packs for invoices, POs, KYC, medical forms, and contracts. Instead of chasing silver bullets, we align quick wins with a durable architecture so each win compounds. We prioritize controls (logging, approvals, and role-based access), build for retries and idempotency, and keep humans in the loop only where their judgment moves the needle.
What does good look like? 70–90% straight-through processing on stable forms; 60–80% reduction in manual keying effort; faster onboarding and payment cycles with fewer exceptions. Beyond percentages on a slide, these outcomes translate to real capacity unlocked, clearer accountability, and fewer fire drills. Your teams spend more time on analytics, exception strategy, and customer value—and less time on swivel-chair tasks.
Business outcomes you can bank on
We also focus heavily on adoption. The best automation fails if it isn’t used. That’s why we co-design runbooks with operations, embed clear SLAs and escalation paths, instrument metrics that teams actually care about, and train champions who sustain the program. We aim for a cultural shift: process improvement becomes a habit, not a one-off initiative.
Security and compliance are first-class citizens in our designs. From secrets management and least-privilege access to tamper-evident logs, we architect automations that stand up to audit scrutiny. We document every interface, assumption, and fallback so that risk teams are partners, not blockers.
How we drive adoption and govern for scale
Finally, we obsess over total cost of ownership. Automations should be easy to operate and cheaper to maintain quarter over quarter. We standardize components, templatize patterns, and build ROI dashboards so sponsors can see impact in hours saved, backlog burn-down, and error reduction.
Our approach in a nutshell:
- Models tuned for low-lighting scans and skewed/rotated images
- Regex+LLM hybrid validators for amounts, dates, tax, and IDs
- Plausibility checks against ERP/MDM to avoid out-of-policy posts
- Active learning pipelines to improve accuracy month over month
Operating model & Center of Excellence
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.
Implementation approach
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.
Pricing & ROI
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.
Proof in action
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.
