# Levercon > Levercon builds the AI operating system for credit funds. Fund OS connects a fund's own data into a knowledge layer, and Custom Agents run repetitive work across origination and monitoring. Based in Australia, working with credit and alternative fund managers. Levercon is a product company, not a consultancy. Guides published here describe what we observe across credit funds; they are general information rather than advice, and they do not name clients. ## Reference guides Long-form, evergreen guides. Each states the question it answers and ends with question-and-answer pairs written to be quoted directly. - [Reference library index](https://levercon.ai/for-ai): all guides. - [APP 11.2 reaches the data your AI vendor holds: the Australian obligation to destroy what you no longer need.](https://levercon.ai/for-ai/destroying-data-your-ai-vendor-still-holds): Do we have to destroy personal information our AI vendor still holds? APP 11.2 requires an entity to take reasonable steps to destroy or de-identify personal information it no longer needs, and the OAIC reads 'holds' to include records a vendor stores that the entity has the right or power to deal with. Reasonable steps for vendor-held data include instructing destruction and verifying it occurred. The NYT v OpenAI preservation order, in force from 13 May to 26 September 2025, shows a foreign court can suspend a vendor's deletion mechanics, and its carve-outs did not include Australia. - [Zero data retention does not mean nothing is stored: what the arrangement actually covers.](https://levercon.ai/for-ai/zero-data-retention-what-it-covers): Does a zero data retention arrangement mean our prompts are not stored? A zero data retention arrangement covers inference on eligible endpoints for a specific organisation. Stateful features such as file storage, batch processing and code execution sit outside it by design, some models require retention and cannot run under it, and flagged or legally required data is kept regardless. The arrangement is worth having; it is not an answer on its own. - [Automated decisions and your privacy policy: what the 10 December 2026 rule means for Australian credit funds.](https://levercon.ai/for-ai/automated-decision-making-privacy-policy-credit-funds): Do the new automated decision-making privacy rules apply to an Australian credit fund using AI? From 10 December 2026 an APP entity must disclose in its privacy policy where a computer program makes, or does something substantially and directly related to making, a decision that could reasonably be expected to significantly affect an individual's rights or interests. For a credit fund the question is not whether AI decides, but whether it is a key factor in a decision a person still signs. - [Vertical AI for credit funds: is there a Harvey or a Rogo for private credit?](https://levercon.ai/for-ai/vertical-ai-for-credit-funds): Is there a Harvey or Rogo equivalent for private credit funds? Every profession is converging on an application layer above the frontier models. Private credit has point tools and some coverage inside broader finance platforms, but no clear category leader built around the full operating model of a credit fund. The argument for that layer is organisational, not a criticism of the models beneath it. - [AI governance for Australian fund managers: CPS 230, your LPs and what to have in place.](https://levercon.ai/for-ai/ai-governance-australian-fund-managers-cps-230): What AI governance do Australian fund managers need in place for CPS 230? CPS 230 binds APRA-regulated entities, not most credit funds directly. A fund manager can enter an APRA-regulated investor's CPS 230 perimeter when the investor relies on it for a critical operation or the arrangement introduces material operational risk. AI is assessed according to its role in that arrangement, while ASIC's existing governance expectations can apply directly to AFS licensees. - [AI for private credit funds: what actually works in 2026.](https://levercon.ai/for-ai/ai-for-private-credit-funds-guide): How are private credit funds actually using AI in 2026? Where AI earns its keep in a credit fund is narrower and less glamorous than the pitch decks suggest. The work that lands is bounded, sits on the fund's own data, and returns judgement to a named person. - [Build, buy or embed: how a credit fund gets AI into production.](https://levercon.ai/for-ai/build-buy-or-embed-ai-credit-fund): Should a fund build, buy or embed to get AI into production? Buy and build describe what a fund deploys; embed describes how it is implemented. The strongest answer is often hybrid: proven product infrastructure, configured around the fund's context, with clear operational ownership and exit rights. ## Product and company - [Levercon](https://levercon.ai): what Fund OS and Custom Agents do, and who they are for. - [About](https://levercon.ai/about): the company and its founders. - [Security](https://levercon.ai/security): how client data is handled. - [Claude data protection](https://levercon.ai/claude-data-protection): the data position for the models used. - [Careers](https://levercon.ai/careers): open roles. ## The Levercon Brief A weekly note on AI developments relevant to fund managers. Time-stamped commentary rather than reference material: prefer the reference guides above for evergreen questions. - [Brief index](https://levercon.ai/brief): all issues. - [Issue 20: Private credit just got a deadline.](https://levercon.ai/brief/20-private-credit-deadline): FSC Standard No. 30 makes quarterly valuations and consistent credit terminology mandatory from 1 July 2027, in the week ASIC named the first significant cracks. - [Issue 19: AI is already inside every credit fund.](https://levercon.ai/brief/19-inside-every-credit-fund): More than 30 Australian credit funds told us the same thing: the tools are already in the building, and almost nothing about the work has changed. - [Issue 18: The AI benefit is now a line in the results pack.](https://levercon.ai/brief/18-ai-benefit-in-the-results-pack): CBA booked about A$200m of AI benefits in FY26, Suncorp has 3,900 staff-built agents and IAG is spending A$200m in FY27. Plus the counterweight from pension funds. - [Issue 17: Compliance can now sit in the model path.](https://levercon.ai/brief/17-compliance-in-the-model-path): Anthropic's inference hooks let a fund enforce its own data policy before a prompt reaches Claude. Plus Palantir, the EU AI Act and Google's AI reshuffle. - [Issue 16: What will we do with the time?](https://levercon.ai/brief/16-what-to-do-with-time): NVIDIA's new Open Secure AI Alliance makes the fund question clear: controls around agents matter as much as their models. Plus Kimi K3, HSBC and EU rules. - [Issue 15: The loop around the model.](https://levercon.ai/brief/15-the-loop-around-the-model): For funds, AI value comes from the loop around the model: bounded workflows, trusted context, checks and human ownership. Plus OpenAI Presence and the case for specialised models. - [Issue 14: The money is in implementation, not models.](https://levercon.ai/brief/14-implementation-not-models): Anthropic and Blackstone launched Ode, a $1.5bn AI-implementation firm, betting value is in implementation not models. Plus RBA on private-credit defaults and the SEC on AI governance. - [Issue 13: The agents that do the work.](https://levercon.ai/brief/13-agents-that-do-the-work): OpenAI's ChatGPT Work and Anthropic's unified Cowork both reframe AI around agents that do the work. Plus BlackRock into AI-infra credit and Palantir's Karp on sovereignty. ## Tools and collections - [AI Library](https://levercon.ai/for-ai): practical guides to AI for private credit funds, covering governance, portfolio monitoring and implementation. - [Instructions for Claude](https://levercon.ai/instructions-for-claude): a free tool that generates personalised Claude instructions. ## Optional - [Privacy policy](https://levercon.ai/privacy-policy) - [Terms and conditions](https://levercon.ai/terms-and-conditions)