Gradient Disco helps organisations build proprietary, sovereign and sustainable AI capabilities - optimised to your processes, running on any infrastructure, and compounding in value with every model generation.
We see these challenges across industries - in companies, public sector organisations, and NGOs that have invested in AI but are not getting what they expected.
Prompts and agent configurations tuned manually to a specific model break when the next version ships. Because the tuning was done by hand, re-tuning is a manual project - with the same cost and uncertainty as the first time, every time.
Token costs scale with every use case you add. API pricing is volatile. Model availability is not guaranteed. What starts as a pilot budget becomes a structural dependency you cannot easily walk back.
When your processes, documents, and customer data flow through hyperscaler models, you are not just using a service - you are training your future competition. Customers, transactions, and operating knowledge become someone else's asset.
Most AI projects spend the first year building infrastructure. Use cases come last - often with off-the-shelf prompts. By the time the platform is ready, the budget is spent and the results are hard to justify.
Gradient Disco turns your organisation's data and processes into proprietary AI - optimised automatically, deployed on your terms, and designed to handle uncertainty at every step. Model the inputs, outputs and quality metrics instead of getting lost in prompts and skills. Let the optimization do the rest.
We work with your organisation to collect what matters - then our optimisation engine runs automatically. The output lives in your artifact registry, fully versioned and auditable. New model available? Your library endures. Simply rerun the optimization and benefit from the improvements.
AI systems are inherently uncertain. Our runtime framework makes that explicit with two methods - picked by deployment context - to calculate an uncertainty value. We use it to decide whether to commit, retry, self-heal, or escalate to a human, based on what being wrong actually costs.
In a dynamic process, where agents collaborate across multiple systems, observing each outcome makes decisions accountable. Every step is a cost-vs-payoff decision. After a burn-in period, the world model enables agents to pick the strongest option. The preferred method for paid-API deployments.
For edge cases, running multiple versions of a model with different input parameters returns a distribution of results, instead of a single output. Measuring the spread of the Ensemble captures the uncertainty inherent in every model output. Not a feeling - a number. Ideal when you run your own compute.
Putting world models and ensembles to action, let your models commit automatically when confidence is high, retry carefully when it wavers, and escalate to a human when the stakes are too high to risk. Our Decision Framework ensures every decision threshold is tuned to the economic cost of being wrong.
AI processes graduate to greater autonomy based on an economic performance function. If signals start diverging in production, the system reverts - automatically, before the damage compounds.
Run several copies, compare.
If they disagree → unsure.
Run once, predict expected.
Big gap to prediction → surprise.
We start where the value is clearest and the entry cost is lowest - and build your AI capital from there.
A sales team creates customer-facing PowerPoint presentations every day - pulling data from previous decks, adapting slide content, applying the corporate template. Done manually with a frontier model, the output regularly breaks the layout, misses brand guidelines, or requires three re-runs to get right. Each rework costs time and money. Each model upgrade resets the prompts.
Where Gradient Disco helpsWe provide a layer of abstraction that focuses on the inputs, the expected outputs, and the quality criteria - and let the system generate the most efficient prompts and skills, creating a valuable data asset that persists beyond model versions and works across providers.
A client has millions of documents - contracts, technical files, product descriptions, regulatory filings - that need to be enriched with structured metadata and have specific facts extracted from them. Running this through a frontier model API is prohibitively expensive, raises data privacy concerns, and requires a new manual setup every time the model is updated.
Where Gradient Disco helpsWe provide a layer of abstraction that focuses on the inputs, the expected outputs, and the quality criteria - and let the system train an open source model to the use case. This creates a durable AI asset that provides a competitive advantage and can complete the task at predictable cost.
Frontier model providers are moving fast - and not just on capability. They are building consulting arms, entering joint ventures with private equity firms, and beginning to differentiate access to their most capable models based on commercial relationships. Equal access to cutting-edge AI cannot be assumed.
At the same time, open-source and smaller models are closing the performance gap with frontier labs faster than most organisations realise. The conditions now exist to run highly capable, task-specific AI on your own infrastructure - at a fraction of the cost, with full control over your data.
Your processes, customer data, and domain knowledge are your competitive advantage. Every interaction with a third-party model is a transfer of that knowledge to infrastructure controlled by others. A sovereign AI stack keeps it inside your organisation.
Organisations that build around a single vendor are exposed to pricing changes, access restrictions, and commercial dynamics outside their control. A methodology that works across model families gives you real options - now and as the landscape evolves.
Organisations that start building proprietary AI capital today - their own training data, their own optimised models - are creating a durable structural advantage. The cost of waiting is not standing still. It is increasing lock-in and a widening gap to catch up.
Not a platform project. Not a prompt consultancy. A structured approach that builds durable AI capital.
We are a small team by design. You work directly with the people who built the methodology and wrote the code. We believe in lean, transparent and effective project work and prefer tangible results over shiny presentations.
Julian has spent the past decade working on machine learning systems - from research to production. He has trained models, built agentic pipelines, led engineering teams, and previously ran a company in the AI space. He designed the optimisation methodology at the core of Gradient Disco and builds the technical infrastructure for every engagement. As a seasoned tech advisor, Julian is the right person to help design your future proof AI stack.
Gregor's background spans AI, consulting, and large programme delivery across Austria and internationally. He has led teams on digital transformation projects, worked on AI strategy and implementation across a range of sectors, and held management roles with full P&L for delivery teams of up to 300 people. He works directly with customers from the first conversation through to delivered results. As a strategy and transformation advisor, he helps organisations build sustainable tech and leadership structure that allows them to grow in a volatile and unpredictable world.
We work with a small number of organisations at a time to ensure the depth the approach requires. Reach out to start the conversation.
Tell us about your organisation and the AI challenge you are facing. We will get back to you within 48 hours.
Based in Vienna, Austria. Working across the EU.
Work with us to create proprietary, sustainable AI that compounds in value over time and builds your own AI IP.
Deploy AI assistants like OpenClaw and Hermes Agent to automate your work - but without the hassle of self-hosting, and with solid guardrails.
If you want AI transformation to accelerate, your team will need hands-on experience and the freedom to experiment. We set up "The Lab" in your organisation, work with your team and provide the guidance so this process cuts the curves and dead ends.
In a world of fast-moving tech, geo-economic disruptions and rapid commodification, it's crucial to build on a strategy that creates redundancies and allows your organisation to benefit from change. We provide a fresh perspective and guidance - discreet, vendor neutral and down-to-earth.
