The rules come first.
Each industry and each country sets terms for customer data, models and outsourcing. Until they are mapped, risk and compliance teams cannot approve a production rollout.
Enterprise AI for Regulated Industries
Take AI from pilot to production, inside the rules your industry runs on.
SuperBrains brings forward-deployed engineers and an enterprise-ready AI platform. Together they take an organisation from its first use case to AI in production. Governance, data security and sovereign deployment are set up before the first agent goes live.
Pilots in manufacturing, banking and telecommunications First production workload targeted in four to six weeks
How an engagement runs
- 1
Strategy and roadmap
Find the use cases that matter.
- 2
AI foundations
Set the rules before the first build.
- 3
Build and deploy
Put the first workload into production in four to six weeks.
- 4
Scale and run
Later use cases start on the same foundations.
Certified SOC 2 Type II · ISO 27001 · ISO 42001
Deploys in SuperBrains Cloud · your cloud · your data centre · air-gapped sites
The Problem
In regulated industries, AI pilots stall before production.
Gartner expects at least 30% of generative AI projects to be abandoned after proof of concept by the end of 2025. Among the causes it names are inadequate risk controls and unclear business value.
Some data cannot leave.
Customer, financial and engineering data often has to stay in the country, the network or the building. Many AI tools assume it can travel.
No one runs AI at scale.
Without a governance framework and a team to run it, approvals start again for each use case.
AI does not know the business.
A business runs on what its people know, and its AI knows none of it. Agents repeat work the business has done before.
What SuperBrains Does
A partner and a platform, from strategy to production.
Strategy, foundations, build and rollout are delivered by one team, on one platform designed for regulated work.
Forward-deployed engineers.
Engineers and AI specialists join your teams on site. They identify the use cases worth doing, set up governance and an AI Centre of Excellence, then build, deploy and hand over.
See How We WorkAn enterprise-ready AI platform.
Agents, workflows, business applications and models run on one governed platform, with data security, access control and audit built in. It runs in SuperBrains Cloud, in your cloud, on your servers or fully air-gapped.
Explore the PlatformIntelligence that keeps learning.
The platform holds the enterprise's knowledge, memory and skills. It continues to learn after go-live and lets out-of-date knowledge fade.
About the Intelligence LayerHow We Work
Foundations first, then use cases.
- 1
Strategy and roadmap
Find the use cases that matter.
Business, risk and IT leaders score candidate use cases on value, feasibility and risk, and agree a roadmap with a business case for the first one.
- 2
AI foundations
Set the rules before the first build.
Our team maps the regulations and data rules that apply in your industry and countries, writes the AI governance framework and sets up your AI Centre of Excellence.
- 3
Build and deploy
Put the first workload into production in four to six weeks.
Agents and applications are built into the business process, tested, approved and rolled out with the people who use them.
- 4
Scale and run
Later use cases start on the same foundations.
Your Centre of Excellence runs the pipeline, and your team takes ownership as ours steps back.
Sovereign AI
Run AI where your data has to stay.
SuperBrains can run entirely inside your data centre or private cloud, including sites with no outbound connection. Open-weight models run on your own hardware, chosen for each use case, so prompts and documents stay inside your network.
Air-gapped deploymentOpen-weight models on your hardwareLocal search and embeddingsYour keys, your logs, your region
- SuperBrains Cloud Managed by SuperBrains, in the region you choose
- Dedicated Single-tenant, managed by SuperBrains
- Your cloud In your own cloud account
- On-premises In your data centre
- Air-gapped In your data centre, with no outbound connection
Security and Governance
Data security and governance, built in.
Controls run inside the platform on each request, and the evidence is kept for your auditors and regulators.
- Identity and access.
- Single sign-on, multi-factor authentication and SCIM provisioning. An agent can reach only the data and tools that the person using it is allowed to reach.
- Data protection.
- Personal data can be replaced with labels before any model receives it, including names written in Indian scripts. Data is encrypted in transit and at rest, isolated by tenant and not used to train models.
- AI controls.
- Prompt-injection checks, red-team checks on each agent draft and guardrails set per agent. If a governance check cannot run, the request stops and the user is told why.
- Oversight.
- Workflows can pause at a step until a named person approves it. Knowledge the platform extracts is queued for your team to review.
- Audit and evidence.
- Each step an agent takes is recorded with its prompt, the context it used and the person who asked. The record is signed and can be exported to your security monitoring.
Industries
Built for industries where knowledge and rules decide the outcome.
Manufacturing.
Engineering knowledge, drawing automation, design calculations and plant troubleshooting, deployed inside your network.
Available: engineering knowledge assistants · drawing automation from reference designs · design calculations run as code.
ManufacturingBanking and financial services.
Early-warning surveillance, credit and collections, compliance and audit, with customer data kept in the country.
Available: early-warning application for lending books · risk and compliance agents · financial and IT audit agents.
Banking and Financial ServicesTelecommunications.
Credit control and collections, enterprise sales and service, under subscriber-data rules.
Available: credit control and collections application · market sizing, survey tracking and renewal agents for enterprise sales.
TelecommunicationsCase Studies
Early work with regulated enterprises.
Banking and Financial Services
Scaling to productionNBFC lending and collections
- Challenge
- Credit and collections teams applied policy case by case, and early signs of stress were found late.
- What was built
- Early-warning rules over the loan book, with an AI copilot that explains each alert and helps the case owner investigate it.
- Result to date
- [client-approved result]
Telecommunications
Production readyEnterprise sales and service
- Challenge
- Sales and service teams worked from separate scripts and systems.
- What was built
- Sales agents that turn account insight into consistent conversations across channels, with opportunity sizing and renewal tracking for enterprise accounts.
- Result to date
- [client-approved result]
Manufacturing
Scaling to productionR&D and process engineering
- Challenge
- Decades of engineering judgement sat in drawings, test data and the experience of senior engineers.
- What was built
- An engineering knowledge layer and agents that give R&D teams access to prior designs, test data and process knowledge, running inside the client's own environment.
- Result to date
- [client-approved result]
Banking and Financial Services
PilotWealth management
- Challenge
- Relationship managers rebuilt client context before each review.
- What was built
- Relationship-manager and portfolio agents that work from the same memory of client context, mandates and past decisions.
Financial Services
PilotVenture capital
- What was built
- A digital workforce of agents that carries deal research through onboarding and reporting.
Client names are available under NDA.
Why SuperBrains
What regulated enterprises get from one partner.
-
Partner and platform together.
Strategy, foundations, build and rollout come from one team, on its own platform.
-
Foundations before use cases.
Governance, the compliance map and your Centre of Excellence are in place before the first build.
-
Sovereign by design.
The same platform runs in our cloud, in yours, on your servers or air-gapped, with open-weight models where you need them.
-
Intelligence that keeps learning.
Agents start from what your organisation has decided, and out-of-date knowledge fades on schedule.
-
Built for local rules and languages.
The data rules in each country you operate in are mapped from the start, and personal data written in Indian scripts is protected before any model sees it.
Next Step
Start with a discovery session.
A working session with your business, risk and IT leads. Together we look at where AI could matter most, what your rules require and what a first production workload would take.
Bring one process and the people who own it.