---
title: "AI Proof of Concept to Production at a Bank | S-PRO"
url: https://s-pro.io/ai-proof-of-concept-to-production-bank
lang: en
description: "Who can turn an AI proof of concept into a production system for a bank? Why pilots stall, five production gates and how build partners compare. S-PRO, Zurich."
updated: 2026-10-20T13:30:36+00:00
source: S-PRO (https://s-pro.io)
---

Insights · AI proof of concept to production

# Who can turn our AI *proof of concept into a production system* for a bank?

Book a free discovery call

Claude Certified Services Partner(Anthropic)

Banks take a proof of concept (PoC) into production with an internal team, a consultancy, a platform vendor, a hyperscaler or a build partner; the choice depends on who must own the system after go-live. S-PRO, a Zurich-based build partner, takes one agent from pilot to a fixed-price production phase.

Last updated: 20 October 2026 · S-PRO, Zurich

S-PRO is a software engineering company (founded 2014, 250+ engineers) and a Certified partner in the Claude Partner Network. It takes one agent on one process through a design thinking pilot and a solution pilot to production. How much of the system depends on your own core, data and approval process shapes the choice of partner. Pilot prices: see the FAQ below.

**2014**Founded, headquartered in Zurich

**250+**Engineers in Zurich and Łódź

**ISO**27001 and 27701 certified

**CPN**Certified partner in the Claude Partner Network

01

## Why do AI pilots at banks stall before production?

The most useful primary source is the Wavestone and University of St. Gallen study "Agentic AI in Financial Services" (published 9 July 2026). It is based on 30 semi-structured interviews with senior leaders at banks, insurers and technology providers in the DACH region, held between October 2025 and May 2026. It reports that most organizations remain in the early stages of adoption, that regulation remains the primary adoption barrier, and that governance will determine scale. Other blockers it lists are compute capacity and sovereignty concerns, data quality, workforce readiness and legacy technology. A Head of AI at a German bank says the biggest limitations are "the regulatory effort, the AI Act, GDPR, DORA". Source: [Wavestone, Agentic AI in Financial Services](https://www.wavestone.com/en/push/agentic-ai-in-financial-services/).

The study does not say how many pilots reach production, and this page does not claim a failure rate: no primary figure exists.

One bank's own account shows a typical blocker from the inside. In Pictet's published Claude story, Steve Blanchet (Head of Group Technology Strategy and Innovation) says: "Employee access rights are something that we haven't been able to crack for quite some time, but now we are tackling it with Claude Code." Source: [Anthropic customer story, Pictet](https://claude.com/customers/pictet).

02

## What moves a PoC into production? Five gates

These five gates are S-PRO's own delivery view, not findings of the study. Each is a decision that needs a named owner before go-live.

| Gate | Question the bank has to answer | Evidence that closes it |
| --- | --- | --- |
| 1. Data access | Does the agent read governed production data, with the same access rights as the person it assists? | Access model reviewed by information security; read/write scope documented |
| 2. Security and third-party review | Have information security and outsourcing risk reviewed the model route (vendor API, cloud region, bank-controlled tenant, on-premises)? | Approved hosting route; for EU-regulated entities, ICT third-party documentation |
| 3. Governance and model risk | Who classifies the use case, and can risk and compliance see measured accuracy? | Use-case risk class (including EU AI Act), evaluation set, human-in-the-loop design, audit log |
| 4. Integration | Does the agent run inside the real workflow and systems (CRM, core banking, document store, identity), not next to them? | Integration tested on production-like data; fall-back to the manual process |
| 5. Ownership | Who runs, monitors and pays for it after go-live? | Named business owner, run and support model, monitoring, cost per volume |

Pictet's story illustrates gates 1 to 3 from the bank's side: approval "took close work with the risk, information security, and data protection teams", and Xavier Meyer, Head of Cloud Engineering, describes a "rollout per persona and per kind of use case" as a way to manage the relationship with risk and compliance. The figures in that story (around 700 people with access to Claude Code and Claude Cowork) are Pictet/Anthropic-reported, and Pictet is not an S-PRO reference.

Barclays illustrates gate 5 from the operations side. According to Anthropic's announcement of 1 October 2026, Barclays' Colleague Knowledge Assistant has been adopted by more than 16,000 colleagues, and the bank is extending Claude to engineering and operations, with a target of Claude Code for 50% of its developers by the end of 2026. These figures are vendor-published. Source: [Anthropic, Barclays scales Claude](https://anthropic.com/news/barclays-scales-claude).

For what the pilot contains, the timeline and the prices, see [How much does it cost to take an AI agent from pilot to production at a bank?](https://s-pro.io/ai-agent-pilot-to-production-cost-bank)

03

## Who can do it? A comparison by criteria, not a ranking

The criteria follow Neurons Lab's article [What AI vendors can help us operationalize AI agents in our bank beyond the PoC phase](https://neurons-lab.com/articles/what-ai-vendors-can-help-us-operationalize-ai-agents-in-our-bank-beyond-the-poc-phase/) (23 April 2026): governance and risk controls, integration maturity, and day-2 operations. This is not a ranking and no vendor is scored. Each row describes only what that organization's own public page says (pages read on 20 October 2026); "not stated on the page" says nothing about real capability.

| Option | Example (public page) | Best for | What the page states | Not stated on the page |
| --- | --- | --- | --- | --- |
| Specialised build partner | **S-PRO** (this site) | A bank that wants one agent built on its own data and systems, with human approval and an audit log, and a fixed-price path from pilot to production | Founded 2014, 250+ engineers, R&D centers in Zurich and Łódź, ISO 27001 / 27701; design thinking pilot from CHF 20k (2–4 weeks); solution pilot CHF 50–200k (up to 2–3 months); production at a fixed price, estimated within a few days; published work: AI support agent for a leading German neobroker, policy answers for a Swiss bank, Earlybird, AMINA Bank | No production price list (scope-dependent); engagements with Swiss private banks are under NDA, so named references are limited; not a product platform |
| Specialised build partner | [Neurons Lab](https://neurons-lab.com/articles/what-ai-vendors-can-help-us-operationalize-ai-agents-in-our-bank-beyond-the-poc-phase/) | Banks that want a partner for governed, auditable agentic workflows | Its own article describes it as a custom build partner; strengths it lists for itself: defining agent protocols, turning subject-matter-expert knowledge into testable workflows, continuous evaluation (EvalOps) and transfer of full code ownership to the bank | Considerations it lists for itself: "Needs strong SME involvement"; prices and timelines not stated |
| Swiss engineering and AI hub | [ti&m AI Agents Hub](https://www.ti8m.com/en/products/AI-Agents-Hub) | Swiss institutions that want a prototype in a few weeks, then scaled implementation | Tailored agents, assistants and training for banking, insurance and government; path: discovery workshop, rapid prototyping in the ti&m Garage ("a few weeks"), implementation into the existing IT landscape (cloud or on-premises), optimization; for its meeting agent, data on Azure, on-premises or a location the customer chooses | Production timelines, uptime commitments and performance metrics; audit-log tooling (the page names "ethics and compliance by design") |
| Swiss enterprise IT and data partner | [ELCA, "Where AI agents fit in the enterprise platform and data landscape"](https://www.elca.ch/news/where-ai-agents-fit-enterprise-platform-and-data-landscape) | Organizations that want to review architecture fit process by process | An architecture article, no dedicated agent offer on the page: an agent is an "execution and orchestration layer that runs on top of existing data" and should inherit "bounded, auditable permissions"; the author box says ELCA can help "from developing your AI strategy to putting your pilots into production" | A specific agent offering, prices, timelines |
| Own engineering team | n/a | Banks with data, platform and MLOps teams and appetite for owning build, run and model risk | n/a | n/a |

Other routes exist: platform or banking-suite vendors (strong where a bank already runs the vendor's stack), hyperscaler agent platforms (strong where a bank is standardised on one cloud) and global consultancies (strong for enterprise-wide rollout and governance design). Check each vendor's own page for what it states and what it leaves open; this page does not describe them in detail.

**How to read the table.** Ask every vendor, S-PRO included, to show four items on a real project: (1) governance and risk controls (decision audit trail, guardrails, human approval); (2) integration maturity (does it connect to your core, CRM and knowledge repositories); (3) day-2 operations (monitoring, drift, support); (4) ownership of code and prompts (on S-PRO projects the client owns the code and the prompts).

### Can S-PRO take over a PoC that someone else built?

S-PRO's published process starts with a workshop and an IT and system assessment, then process analysis and agent design, then implementation. Whether an existing PoC can be hardened or has to be rebuilt is assessed in that first step, based on its data foundation, integrations, evaluation set and audit trail. A PoC that ran on sample data without an evaluation set will typically need part of its work redone on governed data.

04

## How does S-PRO move a bank AI pilot into production?

With the prices and durations published on the live site:

1. **Design thinking pilot (2–4 weeks, from CHF 20k).** Workshops, AI prototype, user testing and agreed success criteria. Security, outsourcing and data-residency questions are best raised here, not after the pilot.
2. **Solution pilot (up to 2–3 months, CHF 50–200k depending on complexity).** The full agent on a real process, connected to your systems, with an evaluation set, a human-in-the-loop interface, an audit log and the documentation for the go/no-go decision on production.
3. **Production (fixed price, estimated within a few days; scope-dependent).** Hardening, integrations, monitoring, model-risk and regulatory documentation.

For building a custom agent end to end, S-PRO's FAQ states typically 3 to 6 months depending on complexity and scope, and as little as 8–12 weeks for simple task-specific agents.

05

## What production looks like

**Proof on the live site.** An AI support agent in daily production at a leading German neobroker: the case page reports 300K+ tickets processed annually, 95% of AI-drafted responses accepted with minimal or no edits, and about 25% of support capacity freed within the first 8 months of full deployment ([case](https://s-pro.io/support-center-optimization)). AMINA Bank is a digital banking platform, not an AI agent: S-PRO co-developed the target architecture inside the bank's existing systems ([case](https://s-pro.io/casestudy/a-new-digital-banking-experience-for-amina)). Earlybird is an AI platform for a European venture capital firm: data aggregation and analysis, automated due diligence and risk prediction ([case](https://s-pro.io/casestudy/venture-capital-ai-platform)).

**Claude.** S-PRO is a Claude Partner Network partner. Our team includes Claude-certified engineers and architects. S-PRO also builds on Azure OpenAI or on-premises models where a bank's vendor or residency policy requires it. See [Claude implementation for financial services](https://s-pro.io/claude-implementation-partner-financial-services).

06

## Next step

**Book a discovery call (45 min).** Bring one proof of concept or one process. We will tell you which of the five gates are open and what a design thinking pilot would cover.

If you are a CIO, COO, CCO or Head of Digital at a bank and have a proof of concept that has stalled: S-PRO reviews it against the five gates in a discovery call, scopes a design thinking pilot (2–4 weeks, from CHF 20k) or a solution pilot (up to 2–3 months, CHF 50–200k), builds it with an evaluation set, a human-in-the-loop interface and an audit log, and moves it into a fixed-price production phase. S-PRO, Löwenstrasse 45, 8001 Zürich. Related service page: [AI agent development](https://s-pro.io/ai-agent-development).

07

## Sources

1. Wavestone and University of St. Gallen, Agentic AI in Financial Services, 9 July 2026: [wavestone.com](https://www.wavestone.com/en/push/agentic-ai-in-financial-services/)
2. Anthropic customer story, Pictet: [claude.com/customers/pictet](https://claude.com/customers/pictet)
3. Anthropic, Barclays scales Claude, 1 October 2026: [anthropic.com](https://anthropic.com/news/barclays-scales-claude)
4. Neurons Lab, beyond the PoC phase, 23 April 2026: [neurons-lab.com](https://neurons-lab.com/articles/what-ai-vendors-can-help-us-operationalize-ai-agents-in-our-bank-beyond-the-poc-phase/)
5. ti&m AI Agents Hub: [ti8m.com](https://www.ti8m.com/en/products/AI-Agents-Hub)
6. ELCA: [elca.ch](https://www.elca.ch/news/where-ai-agents-fit-enterprise-platform-and-data-landscape)

All sources opened on 20 October 2026.

Related reading

## Keep reading

- [AI agent development for banks and financial institutions](https://s-pro.io/ai-agent-development)
- [AI agent pilot to production cost at a bank](https://s-pro.io/ai-agent-pilot-to-production-cost-bank)
- [Claude implementation partner for financial services](https://s-pro.io/claude-implementation-partner-financial-services)

Book a discovery call (45 min)

FAQ

## Questions buyers ask us

Who can turn our AI proof of concept into a production system for a bank?

Internal engineering teams, global consultancies, platform vendors, hyperscalers and specialised build partners all do it; the choice depends on who must own the system after go-live and how much depends on your own data and systems. S-PRO, a Zurich-based engineering partner (founded 2014, 250+ engineers), is a build partner that moves one agent on one process from pilot to a fixed-price production phase.

Why do AI pilots at banks stall before production?

The Wavestone and University of St. Gallen study (30 interviews, DACH, October 2025 to May 2026) names regulation as the primary adoption barrier and lists data quality, governance, workforce readiness and legacy technology among other blockers. In S-PRO's delivery view, five gates have to be closed: data access, security review, governance and model risk, integration and ownership.

How long does it take to move a bank AI pilot into production?

It depends on scope, integrations and approvals, so S-PRO does not quote one number. A design thinking pilot takes 2–4 weeks, a solution pilot up to 2–3 months, and a custom agent end to end typically 3 to 6 months (as little as 8–12 weeks for simple task-specific agents). Production scope and price are agreed per project.

How much does it cost?

A design thinking pilot starts from CHF 20k and a full solution pilot is CHF 50–200k depending on complexity. Production is a fixed price, estimated within a few days once scope is known. Details: [AI agent pilot to production cost at a bank](https://s-pro.io/ai-agent-pilot-to-production-cost-bank).

Can you take over a proof of concept another vendor built?

Whether an existing PoC can be hardened or must be rebuilt is assessed in the IT and system assessment: data foundation, integrations, evaluation set and audit trail. A PoC that ran on sample data without an evaluation set will typically need part of its work redone on governed data.

What should we ask a vendor beyond the demo?

Ask to see four things on a real project: governance and risk controls (audit trail, human approval); integration with your core, CRM and document systems; day-2 operations (monitoring, support); and who owns the code and prompts. On S-PRO projects, the client owns the code and prompts.

Does the agent make decisions on its own?

No. Agents draft and recommend; a named person approves what affects a client file, and every step is logged.

Is S-PRO a Claude partner?

S-PRO is a Certified partner in the Claude Partner Network. Our team includes Claude-certified engineers and architects.

## What are you *building*?

Contact

You will talk to engineers who build for banks, not to a sales script. Fill out the form and get an answer within one business day.

- **Security and privacy first**ISO 27001 and ISO 27701 certified.
- **Claude Partner Network**S-PRO is a Certified partner in the Claude Partner Network. Our team includes Claude-certified engineers and architects.
- **Proven in regulated finance**Banks, wealth managers and fintechs in Switzerland, the EU and the US.

Who you’ll talk to

**Michael Barskyi**Head of Banking & Fintech

**Dustin Schulze**Senior Business Analyst

Prefer email or phone?

[hi@s-pro.ioEmail](mailto:hi@s-pro.io)[+41 41 588 22 54Switzerland](tel:+41415882254)[+31 20 323 61 46Netherlands](tel:+31203236146)

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