Service · AI
Run the back-office workflow end to end, not just a demo of it.
We automate the repetitive, document-heavy work your team does by hand — read it, check it against your rules, write it into your systems, and route only the real exceptions to a person. Measured for accuracy before it touches a live transaction.
The automation pipeline
Auditable · measured before it goes live
The real problem
Why so much back-office work still gets done by hand.
Old rules-based bots (RPA) break the moment a vendor changes an invoice layout or a form arrives as a scanned PDF, so high-volume document work stays manual and error-prone.
AI can read documents it has never seen — the steps that defeated rules-based automation. This automates the routine tasks, with people kept on the exceptions that need judgment.
Of paid activities are technically automatable — the routine, document-heavy tasks an AI pipeline can take over.
Of jobs can be fully automated — so this is task automation with humans on the exceptions, not headcount removal.
Where it pays off
Where AI automation actually pays — and what each one delivers.
One pattern, applied to specific high-volume, document-and-rule-heavy processes.
Accounts payable & invoices
Reads invoices in any format, three-way-matches them, and queues clean ones for payment.
Lower cost per invoice, faster cycle time, fewer errors
Claims & application processing
Extracts data from claim forms and emails, validates it against policy rules, and auto-adjudicates straightforward cases.
Shorter turnaround, consistent decisions, capacity freed
Document data entry & extraction
Turns unstructured documents — contracts, forms, scanned paperwork — into structured, validated records in your systems.
No manual keying, a lower data-error rate
Employee & customer onboarding
Collects and verifies documents, provisions accounts, and moves a new hire through each approval step.
Faster time-to-productive, a consistent audited process
Compliance & document review
Screens documents against policy and regulatory rules, surfacing the items that need human judgment with the evidence attached.
Broader coverage, a full audit trail, focus on real risk
Order & fulfillment operations
Processes orders, change requests, and status updates from email and portals directly into your order and ERP systems.
Lower processing cost, fewer fulfillment errors
As of June 2026 · revisit quarterly
What AI automation does to those processes — the measured impact.
Independent industry findings on the technology, cited as third-party evidence — never Silicon Prime's own client results.
Savings land at scale. Organizations that scaled intelligent automation into deployment reported an average 32% cost reduction — up from 24% two years earlier.
Back-office work in reach. In finance record-to-report, ~20% of tasks are fully automatable and nearly 50% mostly so; HR hire-to-retire is roughly 30% and 30%.
Already showing up. 42% of organizations reported cost reductions where they deployed AI — 58% within service operations specifically.
Automation isn't an agent. Bounded, auditable process automation: a defined workflow that handles the routine 80% and escalates the rest — not an open-ended system deciding its own steps.
What's included
What AI automation services cover.
The difference between automation that scales and a pilot that stalls.
Process discovery & ROI scoping
We map your workflows, measure volume and cost, and rank them by payback — including the honest "not worth automating yet" call.
Document understanding & extraction
The intelligent layer that reads invoices, forms, contracts, and emails — scanned and unstructured included — into structured, validated data. Accuracy is measured against your own documents before launch.
Workflow orchestration & decisioning
We encode your business rules and route each item: auto-process the clear cases, hold the ambiguous, escalate the rest. The decision logic is explicit and inspectable — not a black box.
Systems integration
We wire the automation into your ERP, finance, CRM, and ticketing systems through governed, permissioned connections — inside the access controls your security team already runs.
Human-in-the-loop & exceptions
Below a confidence threshold the item goes to a person with the data and flag reason attached, and that correction feeds back to improve the model.
Monitoring, retraining & enablement
We instrument accuracy, throughput, and exception rate, watch for drift, and train your team to read the dashboards, handle exceptions, and own the system.
What you get — all assigned to you
How it runs
How an AI automation engagement runs.
The same delivery model behind all our AI development work — one accountable lead, fixed scope, no handoffs.
STEP 01
Map
Pick the workflow, measure its volume, cost, and error rate, and define the success metrics.
Output: a ranked plan & a baseline to beat
STEP 02
Design
Build the accuracy test set from your real documents, design the extraction and decision logic, and set the escalation threshold.
Output: a golden test set & a target straight-through rate
STEP 03
Build
Develop the pipeline in your own cloud tenant, wired to your systems, with exception routing and the audit trail in place.
Output: a working automation behind your access controls
STEP 04
Run
Shadow mode, then a controlled pilot, then full volume — measured weekly, your team trained to operate it.
Output: a production automation & a team that owns it
The public record
When automation runs on money, correctness isn't optional.
Automating invoices, claims, and records means letting software write into systems where a wrong entry has a price. The clearest proof we engineer for that is a money-moving platform we built end to end.
Transaction infrastructure · $120M+ · acquired 2017
YardClub
We built the marketplace, payments, and transaction infrastructure end to end — software that processed $120M+ before Caterpillar acquired it in 2017. Moving money through a system of record with zero tolerance for a bad write is the exact rigor a financial automation has to clear.
TechCrunch ↗Adjacent evidence — payments and transaction engineering, cited for the money-moving correctness automation demands, not an AI automation engagement.
Silicon Prime is a Stanford-rooted Responsible AI lab, founded 2011, run by founder Kelvin Tran — 20+ years of production engineering, personally accountable for every engagement. We'll tell you plainly when a workflow isn't worth automating yet — which a vendor paid by the bot won't.
Why automate it with us.
Built to scale, not to demo. Deloitte's data shows the savings land only when automation is scaled into production — and shipping reliable production systems, not slideware pilots, is what the Aegis AI discipline is for.
Auditable by design. Decision rules are explicit and every action leaves a trail — so your finance, risk, and compliance teams can follow what the automation did and why, instead of trusting a black box.
Founder-led, one accountable lead. No account managers, no handoffs — the person who scopes the workflow answers for it in production.
Built to transfer. Models, rules, integrations, and code are assigned to you under full work-for-hire IP assignment, and your team is trained to run and extend the automation when we step back.
Where it lands first
Where AI automation earns its keep first.
Fintech & financial services
Invoice processing, KYC document review, and transaction reconciliation, every step audit-logged and rules-explicit.
Fintech software →Healthcare
Claims, prior-authorization, and intake-document processing inside HIPAA-compliant architectures, humans on every clinical-judgment exception.
Healthcare software →Insurance
Claims intake and adjudication, policy-document extraction, and submission triage — straightforward cases auto-handled, complex ones routed with evidence attached.
Insurance software →Retail & multi-site ops
Supplier-invoice processing, order entry, and store-paperwork digitization across locations, standardized and measured.
Operations platforms →Questions buyers ask before they automate.
Thirty minutes · no pitch deck
Ready to take a manual workflow off your team's plate?
Bring the process eating the most hours — we'll tell you honestly whether AI automation fits it, what it takes to build, and what it saves against your current cost.