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AI that ships, not decks.

Most AI projects die as demos. Ours go to production, because we run one ourselves: DigiSign's Content Studio generates finished designs for screens every day. We find the workflow that eats your team's hours, pilot it in weeks, and hand you the receipts.

01 — PROVEN IN PRODUCTION
Proven in DigiSign

The receipts run every day.

DigiSign’s AI Content Studio turns a one-line brief into finished designs — Gemini-backed, drawing on a 336-template remix engine and live data apps for weather, AQI, and flight boards. Every guardrail, eval, and cost decision we’ll recommend for your project is already running in ours.

Read the DigiSign story

DIGISIGN AI STUDIO — TRACE
$ brief: "Weekend offer — 20% off desserts, ends Sunday" → parsing brief ............ ok → layout engine: 3 concepts from 336 templates → palette: warm · high-contrast · menu-safe → headline set: "Sweet deal. 20% off desserts." → export 1920×1080 · ready for your screens done.
02 — THE WORK

The four jobs we’re hired for.

You'd call us when a workflow eats hours your team doesn't have — or when an AI pilot is stuck at the demo stage and needs to reach production.

01

Document & invoice processing automation

RAG and extraction over purchase orders, invoices, and contracts. Manual data entry drops 70–90%, and approval cycles shrink from days to hours. Your team reviews the exceptions instead of retyping everything.

02

Customer support copilot

A copilot grounded in your product docs and ticket history, with a human in the loop. Teams typically deflect 40–60% of tickets — and answer the rest faster, with sources cited.

03

AI agents for back-office workflows

Agents that close the loop themselves: order status checked, reports assembled, CRM records kept clean across systems. Growth stops meaning headcount; staff move from data-shuffling to decisions.

04

Generative content at scale

Product descriptions, promo creative, and signage content produced at production volume — the same motion DigiSign's AI Content Studio runs every day. Marketing output multiplies without multiplying agency spend.

WHO BUYS THIS

COOs and CFOs buying cost-out automation, heads of support buying copilots, CMOs buying content at scale, CTOs buying the platform. Strongest in document-heavy and support-heavy businesses: insurance, logistics, retail, healthcare administration, professional services.

03 — HOW IT RUNS

Discover. Build. Run.

The shape every engagement takes — a short paid discovery, a build you can watch, and a run phase we operate or hand over cleanly.

DISCOVER

1–2 wks

An AI opportunity audit: we map your workflows, score the use cases by ROI and data readiness, and pick one pilot worth building.

BUILD

4–8 wks

Pilot to production hardening: evals, guardrails, human-in-the-loop review, and integration with the systems you already run.

RUN

ongoing

A monthly retainer: model and prompt monitoring, eval regression, cost optimization, and new use cases as they earn their place.

How we scope work

05 — RELATED SERVICES

Adjacent practices.

04

Data Engineering & BI

Pipelines, warehouses, and live dashboards that cut reporting from days to hours.

06 — FAQ

Fair questions, straight answers.

Weeks, not quarters. A 1–2 week audit picks the right first workflow; a 4–8 week build takes it from pilot to production hardening — evals, guardrails, human review, integration with your systems. The pace holds because we run this motion daily inside DigiSign's AI Content Studio.
Most projects sit between a fixed-fee audit and a multi-month build. The drivers are how many systems we integrate, how messy the source data is, compliance requirements, and how much human review the workflow needs. You get a written estimate after the 1–2 week audit.
Yes, it's safe. Your data stays in your environment, is never used to train public models, and access is scoped per project under NDA. We use enterprise API tiers of models like Gemini, where inputs are excluded from training. The same controls run daily inside DigiSign.
We work with Gemini, OpenAI, and open-source models, chosen per workload for accuracy, cost, and data residency. You're not locked in: we build behind a model-abstraction layer, so swapping providers is a configuration change, not a rebuild — and you own all the code either way.
Grounding and guardrails. Answers are generated from your own documents with sources cited, risky actions require a human in the loop, and every release passes an evaluation suite that measures accuracy before customers see it. When confidence is low, the system says so and escalates.
No. We hand over systems your existing engineers can run, with monitoring, evaluation dashboards, and plain-English runbooks. Most clients keep us on a monthly retainer for model updates and new use cases instead of hiring specialists — and everything we build stays yours if you take it in-house.
We baseline before we build: hours spent, cycle time, ticket volume, error rate. Document automation typically removes 70–90% of manual entry; support copilots deflect 40–60% of tickets. You see the same numbers we do — and if a use case won't pay back, the audit says so.
Yes — that's usually the point. We integrate through APIs where they exist and build thin adapters where they don't, so the AI reads and writes to the systems you already run. No rip-and-replace: your ERP stays the system of record; the automation works around it.

LAST UPDATED — JULY 2026

Tell us what's slow.

We'll tell you what we'd build — and what it costs to run.