What we build and run.
Six lines of work, one way of working: audit first, ship gated, operate in the open. Everything here is grounded in automation we run in production today — for clients or for ourselves.
AI customer-service agents
Our flagship line, and the origin of the company. An agent that reads every inbound email, identifies the customer and the order — even when the sender address doesn’t match — pulls live data from your store and payment platforms, and resolves the case in your brand voice.
- Full resolution, not drafts — replies sent, refunds and store credit executed, cases closed.
- A negotiation ladder for returns that most customers accept — keeping items out of return shipping.
- Human takeover detection: flagged senders and edge cases route to your team with full context attached.
- Self-learning where it’s safe: verified facts are remembered; policies stay under your control.
E-commerce operations
The unglamorous middle of an online store is where money leaks: refunds issued twice, orders cancelled on one platform but not the other, payment records that don’t match the storefront. We automate it with the paranoia it deserves.
- Refunds, store credit and cancellations across your store and your payment platforms — with pre-flight checks and idempotency guards so money moves once, correctly, or not at all.
- Order-data hygiene: payment IDs, fulfillment state and customer records kept consistent across systems.
- Every money action is verified against the real processor — not just the storefront’s view of it.
Finance & back office
We run Coldsilver’s own books on this line, which is the most honest endorsement we can offer.
- Bank-first ingestion: transactions land in your ledger automatically, matched to invoices where possible.
- An exception case board for everything that needs judgment — confirm, decline or modify from one screen.
- Invoice generation and intake, VAT preparation, and a continuously current P&L.
- Built on auditable rails — a bookkeeper, or the tax office, can trace every number to its source.
AI-operated media buying
Ad platforms grade their own homework. We run the account against what actually hit your bank — returns, fees and all — optimising real contribution margin, not platform-reported ROAS. Every budget and creative change waits for your sign-off; every move’s euro outcome is measured and shown.
- Optimised to real profit: contribution margin after COGS, fees and returns — held above your break-even, never vanity ROAS.
- Gated, never autonomous with your money: each budget or creative change is proposed with its exact effect and waits for your tap.
- Proven, not promised: a ledger of what we changed and what each move actually earned — losers shown losing.
- Account forensics underneath: tracking diagnosis (is performance really down, or did measurement break?), plus feed and policy issues prioritised by real impact.
Integrations & internal tools
The connective tissue. We’ve built production pipelines across 10+ platforms — storefronts, inboxes, databases, payment platforms, banking, ad accounts and custom APIs — plus the dashboards and small web apps your team actually uses.
- Workflow pipelines on auditable platforms your team can open and read — no black boxes.
- Data stores and dashboards that make operational state visible.
- Webhooks, APIs and custom endpoints where off-the-shelf connectors stop.
Operating AI in production
Anyone can demo an agent. Running one for months, on real customers and real money, is a different discipline — and it’s the one we care most about.
- Monitoring and health audits on live automation, with conversation-quality review for agents.
- Incident response with root-cause analysis — remediation ships through the same gated chain as everything else.
- Every change snapshotted, validated and approved before production; every deployment has a rollback path.
- No silent failures, ever: if something is dropped, rejected or deferred, it’s logged and visible.
Not sure which line your problem is?
Describe the work in a sentence or two. We’ll tell you what we would automate, what we wouldn’t, and why.