AI automation services
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. In your own cloud, measured for accuracy before it touches a live transaction.
Where AI automation actually pays off — and what each one delivers
One pattern, applied to specific high-volume, document-and-rule-heavy processes.
Accounts payable & invoice processing
Reads invoices in any format, three-way-matches them, and queues clean ones for payment. Benefit — 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. Benefit — shorter turnaround, consistent decisions, capacity freed for complex cases.
Document data entry & extraction
Turns unstructured documents — contracts, forms, scanned paperwork — into structured, validated records in your systems. Benefit — no manual keying and a lower data-error rate.
Employee & customer onboarding
Collects and verifies documents, provisions accounts, and moves a new hire through each approval step. Benefit — faster time-to-productive and 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. Benefit — broader coverage, a complete audit trail, reviewers focused on real risk.
Order & fulfillment operations
Processes orders, change requests, and status updates from email and portals directly into your order and ERP systems. Benefit — lower processing cost and fewer fulfillment errors.
What AI automation services cover
The difference between automation that scales and a pilot that stalls.
Process discovery and ROI scoping
We map your workflows, measure volume and cost, and rank them by payback — run as our AI readiness assessment, including the honest “not worth automating yet” call.
Document understanding and data 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 and 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 and exception handling
Human-in-the-loop review is designed in: 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, and 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 when you hire us — all assigned to you
- A working automation in your own cloud tenant
- The document-extraction models and decision rules
- The integration layer into your systems of record
- An accuracy-and-throughput dashboard
- Runbooks and a trained team
The track record behind automation you can put on a live transaction
When automation touches records that move real money, production discipline is the whole game — what we’ve shipped for over a decade:
Silicon Prime is a Stanford-rooted Responsible AI lab, founded in 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.
Why automate it with us
Built to scale, not to demo. Deloitte’s data shows the cost 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.
Questions buyers ask before they automate
How is this different from the RPA we already have?+
RPA follows a fixed script and breaks on anything it wasn’t programmed for — a new invoice layout, a scanned PDF, a free-text email. AI automation adds an intelligent layer that reads and understands unstructured input, then uses your rules to decide and act. In practice we often keep your RPA for the deterministic last mile, with the AI in front handling the messy input.
How do you stop it from making mistakes on real transactions?+
Measurement and a confidence threshold. We build an accuracy test set from your own documents and cases, measure extraction and decision accuracy against it before anything touches production, and run in shadow mode first. Anything below the threshold goes to a person, every action is logged for audit, and we monitor accuracy after launch as your documents and rules drift.
Does this replace our people?+
No — we scope it as task automation with humans on the exceptions, not headcount removal. It takes over the rote work — keying, matching, and routine approvals — and routes judgment cases to your team with the data already prepared. McKinsey finds fewer than 5% of jobs are fully automatable; the realistic outcome is people freed for higher-value work, not eliminated.
How is this different from an AI agent?+
An AI agent decides its own steps toward an open-ended goal; AI automation runs a defined workflow reliably with a human on the exceptions — bounded, auditable, and lower-risk, which is what most back-office processes actually need. When a problem genuinely calls for autonomous decision-making, that’s our agentic AI development work, and we’ll tell you which one your process needs.
How do you handle data security?+
The automation runs in your own cloud tenant under your access controls; integrations use scoped, permissioned connections to your systems of record; and every engagement starts with an NDA and a security review. Business API traffic to the major model providers isn’t used to train their models by default, and we document every data path so your team can verify it.
Who owns the automation when you’re done?+
You do — completely. The extraction models, decision rules, integrations, and code transfer under full work-for-hire IP assignment signed at kickoff, and your team is trained to operate and extend it. Keep us on a reduced retainer or take the keys; the engagement is built around the handover.
What does it cost and how long does it take?+
Most automations reach production in 4–8 weeks under a fixed-scope engagement with one accountable lead. Build cost depends on the workflow’s complexity — our AI development cost guide gives real ranges — and payment is tied to the ROI we scope against your baseline.
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.