Raysol develops precision AI for financial compliance, investment intelligence, and enterprise model governance. Products built from the inside of the problem — not wrapped around it.
Each Raysol product addresses a specific, high-stakes decision layer where generic tools consistently underperform.
Every Raysol product begins with deep domain expertise — not a generic AI wrapper applied to an industry we read about. Our founder spent years inside the industries we build for. The problems we solve are the ones that actually matter.
We build for NSW, Australia, and the global market — with the precision and regulatory depth that local compliance demands and institutional investors expect.
We build from the inside of the problem. Product decisions are grounded in industry reality, not engineering assumption.
Designed to meet Australian regulatory standards from day one — not retrofitted after the fact. In our products, a confident wrong answer is worse than no answer.
Our products integrate with your existing stack. We are the intelligence layer between your data and your decisions — not a replacement for your tools.
We are onboarding pilot partners in NSW. Trade businesses, accounting practices, and institutional investors welcome.
Raysol is a product company. We don't consult. We don't build for others. We build our own products and deploy them where they create the most leverage — in the daily workflows of businesses that cannot afford to be wrong.
Australia has over 2.5 million small businesses. Most are still making high-stakes decisions with incomplete data, manual processes, and tools designed for a different era.
Raysol exists to change that — not through generic automation, but through purpose-built intelligence that understands the precise regulatory, financial, and operational context of every decision being made.
The Raysol team combines construction industry experience, SaaS engineering, accounting expertise, and AI development — closing the gap between what AI promises and what businesses actually need.
We are selectively onboarding pilot partners and early enterprise conversations.
An AI-powered pre-accounting engine that validates contractor payment data before it reaches your accountant — or the ATO. The first purpose-built TPAR compliance layer for Australian trade businesses.
Trade businesses — electricians, plumbers, subcontractors — must lodge an annual Taxable Payments Annual Report with the ATO, declaring all contractor payments. In 2025, over 11,000 businesses were penalised approximately $18 million for TPAR errors and late lodgements.
The root cause is data quality at the point of capture. Contractor records arrive as handwritten invoices, informal receipts, and verbal arrangements. By the time this reaches an accountant, it is frequently incomplete, inconsistent, and non-compliant. Existing tools do not bridge this gap — Xero and MYOB assume clean structured data; Dext digitises individual documents without cross-record validation.
The TPAR Compliance Platform acts as an automated pre-accounting layer, sitting upstream of Xero, MYOB, or any accounting system. It captures financial inputs via email, mobile upload, and document import — then applies a four-stage validation pipeline before anything touches the ledger.
Each feature addresses a specific failure point in the TPAR workflow — not a generic document processing problem.
| Capability | Raysol TPAR Platform | Hubdoc (Xero) | Dext | MYOB |
|---|---|---|---|---|
| Real-time ABN verification | ✓ | ✗ | ✗ | ✗ |
| Cross-record consistency validation | ✓ | ✗ | ✗ | ✗ |
| TPAR-native structured output | ✓ | ✗ | ✗ | Partial |
| Accounting-system agnostic | ✓ | Xero only | Limited | MYOB only |
| Immutable audit trail | ✓ | ✗ | ✗ | ✗ |
| Handwritten invoice support | ✓ | Limited | Limited | ✗ |
| Multi-client practice dashboard | ✓ | Via Xero HQ | ✓ | Via MYOB Practice |
We are onboarding NSW pilot partners now — trade businesses and accounting practices welcome.
A hybrid AI engine combining real-time market signals, fundamental analysis, and sentiment intelligence to generate risk-adjusted stock recommendations for active investors — with full reasoning transparency.
Active investors face an impossible information load. Earnings releases, macro signals, technical indicators, institutional flows, and news sentiment — no individual processes these coherently in real time. Generic screening tools apply static rules to dynamic markets. AI tools built on basic LLMs lack the financial rigour to be trusted.
The result is decisions made on incomplete information, emotional timing, and retrospective rationalisation — compounding into poor long-term performance.
The Stock Recommendation Engine does not replace human judgement — it refines the inputs to it. A hybrid architecture processes technical signals, fundamental metrics, and real-time sentiment simultaneously, producing risk-adjusted recommendations with full reasoning transparency.
Every recommendation includes a confidence range, the primary driving factors, and explicit conditions under which the thesis breaks down. The goal is not to predict the market — it is to help investors ask better questions, faster.
Processed simultaneously, weighted dynamically, and delivered with the reasoning that earned the signal — not just the output.
High-conviction investors managing their own portfolios who want AI-assisted research without delegation of judgement. The tool sharpens the question — you still make the decision.
Small teams without dedicated research infrastructure who need institutional-quality signal processing at a fraction of the cost of a Bloomberg terminal or a research desk.
Emerging managers building differentiated investment processes who want AI as a research layer — not a replacement for portfolio management or investment conviction.
We are seeking a small cohort of beta investors to shape the product before public launch.
Enterprise infrastructure for teams deploying multiple AI models in production. Monitoring, governance, cost attribution, and performance benchmarking unified in a single control layer — model-agnostic by design.
Enterprise AI adoption is accelerating faster than the infrastructure to manage it. Teams are deploying GPT-4, Claude, Gemini, open-source fine-tunes, and custom models simultaneously — often without visibility into cost, performance, or compliance posture across the stack.
The result: uncontrolled API spend, inconsistent output quality, shadow AI deployments, and zero audit trails for AI-assisted decisions. As regulation tightens, this is no longer a technical problem — it is a governance liability.
The AI Control Plane is a model-agnostic management layer that sits above your existing AI infrastructure. It does not replace your models — it gives you total visibility and control over how they run, what they cost, and whether they perform as intended.
A single interface surfaces real-time performance metrics, cost attribution, output quality scores, and policy compliance status across every model and team in your organisation.
Full visibility of AI infrastructure spend, performance, and technical debt across every team — without pulling engineers from their own work to build internal tooling.
A defensible audit trail and policy enforcement layer for AI use across the organisation. Designed for regulated environments in finance, legal, and healthcare.
A management layer that integrates with existing CI/CD and monitoring infrastructure — reducing operational overhead without replacing the engineering tooling your team already trusts.
Strategic oversight of the organisation's AI capability portfolio — model inventory, ROI measurement, and capability gap analysis in one place. The single source of truth for AI investment decisions.
We are speaking with enterprise teams ahead of beta launch. Book a conversation about your AI governance challenges.
Whether you are a trade business, an accounting practice, an investor, or an enterprise team — we are interested in conversations with people who take their domain seriously.
We respond to all enquiries within 2 business days. Pilot programme applications receive a call within 5 business days.