Enterprise AI consulting
From pilot to a system that survives an audit
Digiton is an AI consulting firm that takes agents, retrieval systems and workflow automation into production for large organisations in Europe, and keeps them running under an audit trail.
Enterprise AI fails for a predictable reason: it stops at a pilot. A demo proves a model can do something once. An enterprise needs a system that does it reliably, every day, inside real infrastructure, with controls that satisfy security, legal, and the board. Digiton is an AI consulting firm built for that gap. We design, build, and operate production AI for large organizations in the UK and Ireland, the US, Canada, Australia, and across Europe, from Lisbon, with clients in 8 countries. Delivery is remote and senior, which is why this single page replaced two dozen city pages that said the same thing with a different place name at the top. Average time from signed scope to a system running in production across those engagements is 45 days.
This page argues the pilot-to-production case. For the service and country view, which markets Digiton works in and what an engagement covers, read enterprise AI consulting and implementation in Europe.
What separates enterprise delivery from SMB tooling
An off-the-shelf chatbot or a low-code automation is fine for a small team. An enterprise has different constraints. Integration with ERP, CRM, identity and data warehouses. Regulatory and data-residency requirements. Multiple teams and approval chains, and a low tolerance for an autonomous system going wrong. Enterprise AI is defined by three things SMB tooling skips: production reliability, governance, and measurable return at scale.
The three that actually matter
- Production. Monitored, integrated systems that run in your environment, not a notebook or a sandbox demo.
- Governance. Every agent has a scoped identity, least-privilege access, human approval on irreversible actions, full audit logging, and a kill switch. See our guide to AI agent governance and to agentjacking defense.
- ROI. Scope is tied to a number (hours removed, cycle time, error rate, revenue), measured after launch, not promised in a deck.
Where the engineering detail lives
Enterprise buyers rarely start from "we need an AI agency". They start from a specific problem, so the working detail sits on its own pages rather than being flattened into this one.
- Zapier to n8n migration, budgeted per workflow type, with the four things that break on every migration and the parts of the licence fee that reappear as infrastructure.
- Why self-hosted n8n gets slower as you add workers, on the database bottleneck, connection pool arithmetic, and the four patterns behind workflows that fail silently.
- GDPR-compliant RAG, on erasure that has to reach embeddings and memory, the transfers most mapping exercises miss, and what counts as an adequate citation.
- WhatsApp AI for utilities and public services, on the channel argument, reaching a 1996 billing system safely, and the lawful basis question that decides public-sector deals.
What the EU AI Act actually requires of you in September 2026
The high-risk deadline moved. Regulation (EU) 2026/1744, the Digital Omnibus on AI, entered into force on 27 July 2026 and pushed Annex III standalone high-risk obligations from 2 August 2026 to 2 December 2027, with product-embedded Annex I systems moving to 2 August 2028. Almost every vendor page written before August still counts down to a date that no longer exists.
Three sets of obligations did not move and bind your systems today. Article 5 prohibited practices have applied since February 2025. General-purpose AI provider obligations under Articles 51 to 56 have applied since August 2025. Article 50 transparency duties went live on 2 August 2026 as scheduled, which means disclosure when a user is talking to an AI, machine-readable marking of synthetic media, and deepfake notices. The deferral changed when enforcement starts, not what compliance requires. The detail sits on EU AI Act readiness for enterprises, and the engineering side of it is on GDPR-compliant RAG.
How to evaluate an enterprise AI consulting firm
- Do they run their own AI in production, or only advise? Digiton operates its own product, Parci.
- Do they integrate with your real stack, or only build standalone tools?
- What is their governance model: identity, approvals, logging, monitoring, incident response?
- How do they handle data residency, GDPR, and the EU AI Act?
- Do they price by outcome and start with a paid audit, or bill open-ended hours?
- Will they operate the system after launch, or hand you a prototype to maintain?
How we engage
Every engagement starts with a paid enterprise AI audit: we map the highest-return workflows, the integration surface, and the governance requirements, and return a scoped plan with expected ROI. Then we build in a staging environment, red-team it against hostile inputs, and move it to production with monitoring and a human-override path. You choose whether we operate it or hand it over. The wider operating picture, drawn from live deployments, is in our State of AI Operations 2026 report.
Industries we serve
The work is most valuable where volume, regulation, or complexity are high. We build enterprise AI for financial services, logistics and supply chain, manufacturing, and professional services firms, plus horizontal enterprise workflow automation.
EU-native, built for regulated buyers
Digiton is Lisbon-based and EU-native, which for a regulated buyer is an asset rather than a location: senior European engineering, GDPR and EU AI Act fluency by default, and a partner who works across time zones with UK, Nordic, Dutch and North American teams. Three engagements, described by sector and scale rather than by logo, because the mechanism is the point:
- Municipal water utility, Portugal, roughly 175,000 residents served. A 24/7 WhatsApp assistant reaching a SOAP billing platform built in 1996 and still carrying 1.7 million customers nationally. In production. The lawful-basis question decided the procurement, not the model choice.
- Cultural heritage institution, Angola. More than 60 hours of oral testimony and over 1,000 pages of transcript through RAG pipelines, so the archive stays searchable and every answer resolves to a citable source. Presented publicly at Universidade Aberta, Lisbon, April 2026.
- Email marketing agency, United States, running since August 2025. Production reporting, dashboards and workflow automation. Campaign build time went from four hours to fifteen minutes.
Digiton also runs its own product, Parci, which covers 300 of 308 Portuguese municipalities. Operating a product is what keeps the governance argument honest: we page ourselves when it breaks.
Frequently asked questions
What is an enterprise AI consulting firm?
A firm that designs, builds and operates production AI for large organisations: agents running real workflows, integration into the existing ERP, CRM, identity and data stack, and retrieval over corporate knowledge, with governance and measured return. Unlike a consultancy it ships and runs the system. Unlike off-the-shelf tooling it is built for scale and audit.
How is Digiton different from a strategy consultancy?
A consultancy advises and hands over a strategy. Digiton scopes the opportunity and then builds the system, ships it to production and operates it, so the recommendation does not die waiting for somebody else to implement it.
What does enterprise AI governance involve?
Per-agent scoped identity, least-privilege access, human approval on irreversible actions, immutable audit logging, runtime monitoring, and a kill switch, plus treating tool and data output as untrusted. It is what lets a large organization run autonomous systems without betting the business on an agent's worst day.
Which countries does Digiton work with?
Digiton works with enterprises in the UK and Ireland, the US, Canada, Australia, and across Europe. It is EU-native and multilingual, operating across time zones with full overlap for European clients and working overlap with North America and Australia.
How do you integrate AI with our existing enterprise systems?
Through APIs and connectors to your ERP, CRM, data warehouse, and identity provider, with the AI layer sitting on top rather than replacing what works. Integration and security are part of the build, not an afterthought, so the system fits your stack and your controls.
How do you handle GDPR, data residency, and the EU AI Act?
As default requirements, not add-ons. As an EU-native partner, Digiton designs for GDPR and EU AI Act alignment, supports data residency choices, and builds the logging and human-oversight controls that regulated buyers and auditors expect. Since 27 July 2026 the high-risk timetable runs to December 2027, while Article 50 transparency, the GPAI obligations and the Article 5 prohibitions bind today.
How much does an enterprise AI engagement cost?
Engagements are scoped by outcome after a paid audit, not billed as open-ended hours. Enterprise programmes (production agents, automation, RAG, governance) typically start in the low five figures and scale with the work. The audit fixes scope and expected ROI before you commit.
How long until an enterprise AI system is in production?
A focused first system is usually live within four to eight weeks, depending on integration complexity and approval cycles. Larger programmes run in phases, each shipping a measured win, rather than a single long project that delivers nothing until the end.
Do you operate the AI after it is built?
Yes, if you want. Digiton can hand the system to your team with documentation, or operate it continuously with monitoring, governance, and incident response included. Many enterprises start with operated delivery and bring it in-house once it is proven.
Why choose an EU-native agency over a local one?
An EU-native partner brings GDPR and EU AI Act alignment by default, senior European engineering, and cross-border experience, which matters for enterprises with European operations or customers. The value is compliance and delivery quality, not location-based cost.
What makes Digiton different?
Digiton ships and operates production systems, runs its own AI product (Parci) on the same stack it sells, builds governance in from the start, and prices by outcome. It is an agency that an enterprise can put in front of security, legal, and the board, not a demo shop.
How do we start?
Book an enterprise AI audit. Digiton maps your highest-return workflows, the integration surface, and the governance requirements, and returns a scoped plan with expected ROI, so the first build is grounded before anyone commits budget.
Related
Ready to put AI to work?
Book a discovery audit and we will map the highest-ROI AI agents and automations for your business.
Book a discovery audit