Every invoice read before it’s paid.

Your ERP matches the numbers. A decision model reads every invoice line against your payment rules: new bank details, extra charges, cancelled services.

Use cases

• Invoice checks: Every invoice read against your payment rules before it’s paid: new bank details, extra charges, cancelled services.
• Support inbox: Every reply, refund and close checked against your rules before the customer sees it.
• Marketing compliance: Every campaign piece checked against your advertising rules before it’s published.
• Sales leads: Every demo request and inbound email sorted the moment it arrives, against qualifying rules you rewrite each campaign.
• Grading AI replies: Every answer your AI gives graded against its sources, not a 1-in-10 sample.
• Agent guardrails: Every tool call checked before it runs, and every tool response before your agent reads it.
• Document extraction: Bills of lading and CMR notes read field by field, each value with the line it came from.
• Damage checks: Does the claim photo show the damage and the car the claim says? Checked as it arrives, with a retake asked at once.
• Safety audits: Site and permit photos checked against your own safety list: open edges, scaffold tags, blocked exits, lock and tag.

Industries

• Finance back office: Screening hits, news checks, invoice exceptions and one-off account coding, read first so people decide faster.
• Customer service and e-commerce: Routing and quality checks on every conversation, plus the e-commerce steps around them: listing safety information, reviews, return reasons and the returns desk.
• Logistics and warehousing: Booking checks before the customs filing, carrier emails routed, goods-in photos against the delivery note, dock and doorstep photos.
• Insurance claims: Sorting first notices, spotting vulnerable customers and complaints, checking a claim’s documents are complete, flagging recovery, checking claim photos and videos.
• Software and AI agents: Labelling issues, flagging which areas a change touches, checking screenshots before release, routing requests to the right model, and deciding which night alerts wake someone.
• Manufacturing and construction: Coding failure reports from technician notes, triaging shift logs, checking close-out photos of equipment.

Inputs

• Text: Emails, chats, replies, posts, tool calls. Send the text with your questions, get each answer with how sure Strom is.
• Documents: PDFs, scans and photos of paper. Each field comes from the line that gives it, so checking it takes a glance.
• Images: Up to eight images per request, with text beside them. Ask what they show, whether they match, and where something is.
• Video: Ask your questions of every frame as the video plays, or describe one object and follow it through the whole video.