Last updated 5 months ago
Cardano's budget faces extreme market volatility & complex on-chain dynamics, hindering precise financial planning & proactive risk management, leading to suboptimal resource allocation.
Photrek will use physics-informed AI to analyze Cardano budgets flows, creating probabilistic forecasts and risk profiles to support resilient financial planning and resource management.
This is the total amount allocated to Cardano AI Risk-Manager for treasury financial resilience.
Please provide your proposal title
Cardano AI Risk-Manager for treasury financial resilience
Enter the amount of funding you are requesting in ADA
85000
Please specify how many months you expect your project to last
6
Please indicate if your proposal has been auto-translated
No
Original Language
en
What is the problem you want to solve?
Cardano's budget faces extreme market volatility & complex on-chain dynamics, hindering precise financial planning & proactive risk management, leading to suboptimal resource allocation.
Supporting links
Does your project have any dependencies on other organizations, technical or otherwise?
No
Describe any dependencies or write 'No dependencies'
No dependencies
Will your project's outputs be fully open source?
Yes
License and Additional Information
The project will be fully open source. Photrek utilizes a GNU GPL 3.0 license for software development projects, which requires users of the software to maintain their code as open source.
Please choose the most relevant theme and tag related to the outcomes of your proposal.
Risk Management
Describe what makes your idea innovative compared to what has been previously funded (whether by you or others).
Photrek’s Cardano Financial Genome introduces physics-informed AI for treasury risk management. Unlike standard models assuming bell-curve distributions, our Coupled Variational Inference framework captures heavy-tailed risks and “black swan” events, enabling robust forecasts. We enhance trust with calibrated probabilistic outputs measuring Accuracy, Decisiveness, and Robustness, then translate insights into clear labels and prescriptive recommendations. This bridges complex modeling with actionable financial intelligence for Cardano.
Describe what your prototype or MVP will demonstrate, and where it can be accessed.
Our MVP will demonstrate the Cardano Financial Genome in action, showing how CVI models process real Cardano financial data to produce probabilistic forecasts and actionable risk insights. Users can explore budget projections through three risk profiles: Decisive, Accurate, and Robust, by adjusting the coupling parameter (kappa). The prototype will also classify threshold risks (e.g., treasury balance breaches) with confidence scores. Accessible via APIs/web tools and GitHub, it ensures transparency, interactivity, and verifiable functionality.
Describe realistic measures of success, ideally with on-chain metrics.
Success will be measured by model accuracy, trustworthiness of probabilistic insights, and observable impact on Cardano’s financial governance. Our CVI model will target at least 50% overlap between forecast distributions and historical data, plus a classification score (e.g., F1 ≥ 0.70) for threshold risk detection. Beyond metrics, success includes early warnings of liquidity crunches that inform on-chain actions, reducing cash drag, and building community trust through transparent, verifiable outputs that encourage greater participation in financial governance.
Please describe your proposed solution and how it addresses the problem
The effective management and forecasting of financial flows within the Cardano ecosystem presents a challenge, often exceeding the capabilities of conventional economic models. The inherent volatility of digital asset markets, combined with the intricate mechanics of on-chain treasury flows and the dynamic nature of decentralized governance, creates a complex adaptive system. This environment is characterized by non-linear relationships and heavy-tailed distributions, where rare but impactful black swan events can disproportionately affect financial stability. Traditional forecasting methods, typically rooted in assumptions of Gaussian distributions and linear causality, are fundamentally ill-equipped to accurately capture and quantify the financial risk and potential future states.
Photrek’s proposed solution is a novel, physics-informed probabilistic financial intelligence engine, centered around applying the methods of Coupled Variational Inference (CVI) [5-8]. This advanced AI architecture is suited to overcome the limitations of traditional financial models by explicitly leveraging the non-Gaussian, heavy-tailed nature of economic data and the complex interdependencies of a decentralized blockchain. Our CVI architecture follows the principles of nonextensive statistical mechanics and nonlinear statistical coupling [3], being inherently built to expect and quantify the risk of black swan events such as major market shocks, significant shifts in staking behavior, or unforeseen governance outcomes, that standard Gaussian models are blind to.
The foundational strength of our approach lies in the CVI's ability to learn the underlying latent structure of complex systems. At its core, the model identifies and characterizes the probability distribution of financial states through their fundamental statistical parameters: Location, Scale, and Shape. The Location parameter describes financial flows' central tendency or expected values. The Scale of the distribution captures the measurable uncertainty, spread, and interdependencies between uncertain financial quantities. The shape parameter governs the heaviness of the tails, allowing the model to capture extreme events and outliers. The coupling aspect of the CVI enables the model to account for risks that are not available in limited datasets. For example, it can understand the cascading effect between a decrease in network transaction volume and its subsequent impacts on treasury flows.
The operational flow of our solution starts with comprehensive data aggregation, connecting to Cardano's financial nervous system via direct on-chain data streams and, through collaboration with the Cardano Foundation's financial records, including their Reeve system. This holistic ingestion of verifiable on-chain data and essential off-chain financial information provides the high-dimensional dataset necessary to train the CVI.
Once trained, the CVI forms the probabilistic core of our engine, outputting a high-dimensional probability distribution of possible future cash flow states for the Cardano ecosystem. We can then perform generative simulation and risk quantification by leveraging this probabilistic output. This involves running several Monte Carlo simulations, asking the model to generate different possible versions of what the next days could look like for Cardano's budget. This capability directly supports scenario generation to stress-test and operational changes, allowing stakeholders to explore "what-if" situations and calculate risk metrics (e.g., "There is a X% chance the Cardano Treasury balance will fall below Y ADA in the next Z days", "What if ADA price drops by 50%?", "What if a major protocol upgrade significantly changes network fees?"), and sensitivity analysis to identify the fragile points.
A key innovation in presenting these complex insights is the application of the Risk Profile for probabilistic inference assessment [1, 2, 4]. This methodology allows us to interpret the probabilistic output of the CVI through different lenses of risk sensitivity, ensuring the trustworthiness and calibration of these crucial predictions by varying the nonlinear statistical coupling parameter K [4]:
This nuanced interpretation empowers decision-makers to select the appropriate financial perspective based on their specific risk appetite and operational context.
Furthermore, our solution transitions from a purely diagnostic tool to a prescriptive optimization engine, enhanced by a distinct classification layer. This layer is crucial for translating complex probabilistic forecasts into clear, actionable decisions, aligning with Reeve's goal of providing enhanced reporting and analytics with deeper insights into financial data. This involves deploying robust classification algorithms that interpret the CVI's probabilistic outputs and assign categorical labels for immediate understanding and action. Concrete applications include Anomaly Detection and Risk Triage(e.g. flagging of potential financial irregularities, security breaches, or emerging liquidity concerns), Financial State Classification, Specific Event/Threshold Breach Classification (e.g., minimum treasury balance, maximum spending rate, specific ADA price correlation).
A critical component of our solution, particularly for high-stakes classifications like predicting a threshold breach, is the rigorous assessment of the quality of our probabilistic inferences. Generating a probability (e.g., "5% chance of breach") is only half the battle. The trustworthiness of that probability about whether the model truly states its confidence reliably, is paramount for next generation accountability. We will explicitly utilize the framework presented by Nelson (2017) [4] to continuously evaluate the Accuracy, Decisiveness, and Robustness of our model's probabilistic outputs. This framework, based on generalized means, enables us to understand if our model is consistently over-confident (providing a false sense of security) or under-confident (generating too many false alarms), and to make necessary adjustments. This commitment to calibrated probabilities ensures that the insights provided are verifiably reliable, building critical confidence among stakeholders.
Finally, our solution culminates in a seamless user experience. The complex insights derived from the CVI will be translated into intuitive dashboards. The LLM Integration translates outputs and latent representations into recommended actions, providing actionable guidance. This ensures that the rigorous analysis is accessible for the Cardano Foundation, governance bodies, and the broader community, embodying the vision of a "living document" budget that continuously adapts to real-time events.
By providing a resilient financial planning capability, driven by advanced AI and validated probabilistic insights, our service enables optimized resource allocation, informed governance, and ultimately contributes to the long-term sustainability and ambitious decentralized future of the Cardano ecosystem.
[1] Nelson, K. P., et al. (2011). A risk profile for information fusion algorithms. Entropy, 13(8), 1518–1532.
[2] Nelson, K. P. (2014). Reduced perplexity: Uncertainty measures without entropy. In Recent Advances in Info-Metrics. arXiv.
[3] Nelson, K. P., et al. (2014). Probabilistic graphs using coupled random variables. In SPIE Defense, Security, and Sensing.
[4] Nelson, K. P. (2017). Assessing probabilistic inference by comparing the generalized mean of the model and source probabilities. Entropy, 19(6), 286.
[5] Nelson, K. P., et al. (2017). On the average uncertainty for systems with nonlinear coupling. Physica A, 468, 30–43. https://doi.org/10.1016/j.physa.2016.09.046
[6] Cao, S., et al. (2022). Coupled VAE: Improved accuracy and robustness of a variational autoencoder. Entropy, 24(3), 423. https://doi.org/10.3390/e24030423
[7] Nelson, K. P. (2025). Coupled entropy: A Goldilocks generalization for nonextensive statistical mechanics. arXiv preprint arXiv:2506.17229.
[8] Nelson, K. P., et al. (2025). Variational inference optimized using the curved geometry of coupled free energy. arXiv preprint arXiv:2506.09091.
Please define the positive impact your project will have on the wider Cardano community
The implementation of Photrek's physics-informed probabilistic financial intelligence engine, centered on the Coupled Variational Inference (CVI) architecture and its sophisticated analytical framework, is poised to generate a multifaceted positive impact on the wider Cardano community. This impact extends far beyond financial reporting, directly addressing critical challenges within decentralized finance and aligning with the broader industry's demand for advanced financial tools.
Firstly, our system will cultivate vastly improved levels of transparency and accountability within the Cardano ecosystem's financial operations. By meticulously ingesting and analyzing immutable on-chain data from the Cardano Treasury and Project Catalyst, and by integrating with the Cardano Foundation's Reeve system, the project establishes a robust, verifiable, and auditable financial record. However, transparency in complex systems requires more than just raw data; it demands intelligible and reliable interpretation. Our solution elevates this by providing calibrated and verifiable probabilistic insights, coupled with clear classification outcomes. The rigorous framework for assessing the Accuracy, Decisiveness, and Robustness of our predictions, as defined by Nelson (2017) [4], ensures that the uncertainty inherent in financial forecasting is not merely acknowledged but precisely quantified and communicated. This demystifies complex financial flows, empowering every community member, from individual ADA holders to active DReps, with a clear, evidence-based understanding of where funds originate, how they are disbursed, and the associated financial risks. This level of verifiable transparency builds critical confidence in the stewardship of community resources, shifting focus from merely data gathering to insightful analysis, providing accurate forecasts enabling resilient financial planning, facilitating optimal resource allocation and empowering the Cardano community.
Secondly, this enhanced transparency directly translates into a significant boost in community trust and external confidence. A blockchain ecosystem whose financial health is rigorously analyzed, proactively managed, and transparently communicated, with clearly calibrated probabilities and actionable classifications, is inherently more attractive to external stakeholders. Developers are more inclined to build on a platform with demonstrable financial stability and predictable funding mechanisms. Businesses seeking decentralized solutions will find a more reliable and resilient environment, reducing the "cash drag" caused by inaccurate forecasts that McKinsey & Company (2022) estimated at 2% of enterprise value. This increased confidence fosters a positive feedback loop, drawing in new investment, encouraging greater participation in staking, and stimulating overall network activity, all of which are vital for sustained growth and adoption. Our ability to provide trust in financial predictions will be a key differentiator.
Thirdly, the CVI-driven intelligence, now enhanced by direct classification outputs, will revolutionize decision-making and governance capabilities within the Cardano community. By providing nuanced, probabilistic forecasts and explicit risk profiles (Decisive, Accurate, Robust), the project equips DReps and governance bodies with a comprehensive understanding of potential financial trajectories. This moves beyond the limitations of single-point forecasts, addressing the 78% of CFOs concerned about forecast accuracy (Deloitte 2023). Our system delivers immediate classification results for anomalies, financial health states, or threshold breaches, directly translating complex data into actionable alerts and prescriptive recommendations. For instance, classifying a looming "covenant breach" allows for timely intervention, avoiding costly repercussions. The system’s capacity for real-time analysis and prescriptive recommendations, supporting the vision of a "living budget," ensures that resource allocation is agile and responsive to evolving market conditions and on-chain dynamics, rather than being constrained by rigid, outdated plans. This translates into more effective deployment of community funds towards high-impact projects that drive real-world utility and adoption, supported by transparent, auditable, and calibrated insights. It provides the real-time forecasting tools that 82% of companies plan to invest in (EY Global FP&A Survey 2023), moving Cardano beyond its current reliance on less sophisticated financial management tools.
The Photrek financial intelligence engine is designed to serve a diverse array of stakeholders across the Cardano ecosystem. Its primary users and beneficiaries include:
Furthermore, the project directly contributes to long-term financial resilience and sustainability for the entire ecosystem. By explicitly modeling the heavy-tailed nature of crypto markets using the CVI's ability to characterize Coupled Gaussian distributions, including their mean, variance, and covariance, and by quantifying the probability of extreme financial events, our solution enables truly proactive risk management. The CVAI's inherent robustness in handling outliers means the community can identify potential liquidity crunches or periods of significant financial strain well in advance, even those driven by rare, high-impact occurrences. This foresight allows for the formulation and implementation of timely mitigation strategies, protecting the ecosystem from severe market shocks. A resilient financial backbone, supported by physics-informed statistical understanding of its complex dynamics, is fundamental to Cardano's long-term viability and its ability to achieve its ambitious decentralized future.
What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?
Photrek has a proven track record of delivering high-quality governance tools within the Cardano ecosystem, partnerships with IOG, and the Singularity NET community. Recently, Photrek successfully delivered the initial Cardania AI Agent, which received positive community feedback for its relevance in this phase of Cardano governance. Our team combines domain expertise in Cardano governance, risk analysis algorithms, AI integration and Socioeconophysics to support the Cardano AI Financial Risk-Manager MVP.
Our project has a rigorous, scientific and evidence-based approach, building upon solid and innovative research [1-8] combined with a phased development process. Our commitment to transparency is evident through our public GitHub repository (github.com/Photrek), hosting relevant open-source projects, including those related to Coupled Variational Inference and nonlinear statistical coupling, demonstrating our existing technical prowess.
Additionally, we will engage in continuous consultation with the Reeve team from the Cardano Foundation to align our development with the ecosystem's evolving needs and standards, ensuring practical integration and sustained relevance. This multi-faceted capability and validation strategy ensures that our innovative approach is technically sound, feasible, reliable, and accountable to the Cardano community.
Milestone Title
Data Ingestion and Pre-processing Framework Establishment
Milestone Outputs
Acceptance Criteria
Evidence of Completion
Delivery Month
1
Cost
17500
Progress
20 %
Milestone Title
CVI Core Architecture and Initial Training Protocol
Milestone Outputs
Acceptance Criteria
Evidence of Completion
Delivery Month
3
Cost
25000
Progress
50 %
Milestone Title
Probabilistic Forecasting and Risk Profile Generation MVP
Milestone Outputs
Acceptance Criteria
Evidence of Completion
Delivery Month
5
Cost
25000
Progress
80 %
Milestone Title
Project Close Out
Milestone Outputs
Acceptance Criteria
Evidence of Completion
Delivery Month
6
Cost
17500
Progress
100 %
Please provide a cost breakdown of the proposed work and resources
Milestone 1: Data Ingestion & Pre-processing (Month 1) – ₳17,500
Milestone 2: CVI Core Architecture & Initial Training (Months 2–3) – ₳25,000
Milestone 3: Probabilistic Forecasting & Risk Profile MVP (Months 4–5) – ₳25,000
Final Milestone: Dashboard, Full Codebase & LLM Integration (Month 6) – ₳17,500
Total Project Cost: ₳85,000
How does the cost of the project represent value for the Cardano ecosystem?
Currently, the decentralized financial landscape, including Cardano, is plagued by extreme market volatility and opaque on-chain dynamics, leading to suboptimal resource allocation and significant financial risk. This inadequacy is not unique to decentralized finance; it mirrors broader challenges in the financial sector.
Current market analysis reveals significant pain points. The Association for Financial Professionals 2022 Survey indicates that finance teams dedicate 75% of their time to gathering and validating data from systems, leaving only 25% for strategic analysis. This inefficiency contributes to what McKinsey & Company (2022) describes as an average cash drag of 2% of enterprise value due to missed financing opportunities from inaccurate cash-flow forecasts. The urgency is further underscored by Deloitte's CFO Signals 2023 report, where 78% of CFOs cite forecast accuracy as their top concern, estimating that even a 1% improvement can yield millions in cost savings. Yet, Forrester Research (2021) highlights that 68% of finance functions still rely on outdated spreadsheets or fragmented point-solutions. The demand for innovation is apparent, with EY Global FP&A Survey (2023) finding that 82% of companies plan to increase investment in forecasting tools to support dynamic scenario analysis. Our solution addresses these pervasive issues, moving beyond legacy approaches to establish an intelligent and transparent financial backbone.
The proposed investment of ₳85K for the Cardano Financial Genome project represents an excellent investment for money for the Cardano ecosystem by directly addressing critical financial inefficiencies and proactively fortifying its long-term stability. This cost is a strategic outlay for a robust, cutting-edge MVP solution that moves Cardano beyond conventional financial management practices.
By deploying a novel, physics-informed Coupled Variational Inference (CVI) framework, our project provides precise, probabilistic financial forecasts capable of identifying and quantifying the risk of rare, high-impact "black swan" events. This is a fundamental advancement over traditional models ill-equipped for heavy-tailed crypto markets. Our project, by providing significantly enhanced accuracy and actionable classifications, positions Cardano to realize these substantial savings and optimize its substantial treasury.
Furthermore, this investment cultivates vastly improved transparency and accountability. By providing rigorously calibrated and verifiable probabilistic insights integrated with LLMs, the project demystifies complex financial flows for every community member, fostering critical confidence in the stewardship of community resources. This increased trust and demonstrably superior financial management capability make Cardano inherently more attractive to developers, businesses, and investors, stimulating sustained network growth and adoption. The project cost does not cover only software development but building a resilient financial backbone that underpins Cardano's ambitious decentralized future, ensuring optimal resource allocation, informed governance, and mitigating potentially far greater future losses due to market shocks or mismanaged funds.
Towards that end, Photrek utilizes competitive pricing methods that provide the highest value to our customers and support our team members with fulfilling lives. Our rates are based on self-employment in the US & Canada. The rates take into account the employment overheads of the resources contracted. The amounts are calculated for each milestone based on the hours to complete. For example the chart for engineering and scientific salaries in the Commonwealth of Massachusetts is provided here: https://www.mass.gov/guides/salary-and-compensation.
Terms and Conditions:
Yes
Photrek, a team with extensive experience in complex decision systems, machine learning and blockchain governance, leads this project. Dr. Kenric Nelson, founder of Photrek, provides the foundational scientific and governance expertise, guiding the project's rigorous approach to probabilistic modeling and risk assessment. M.Sc. Igor Oliveira serves as the lead algorithm developer, spearheading the technical implementation of the sophisticated CVI architecture. Juana Attieh, as Product Impact Lead, ensures the solution's strategic alignment with community needs and drives its real-world applicability within the decentralized ecosystem. Eystein Magnus Hansen contributes essential frontend development and expertise in n8n automation for LLM integration, while also acting as a key liaison for collaboration with the Cardano Foundation's Reeve team. Barry Varys, as Project Manager and researcher, oversees project execution and contributes expertise in the governance of decentralized communities, ensuring seamless delivery and strategic direction.
Dr. Kenric Nelson is Founder and President of Photrek, LLC which is developing novel approaches to Complex Decision Systems, including dynamics of cryptocurrency protocols, sensor systems for machine intelligence, robust machine learning methods, and novel estimation methods. He served on the Cardano Catalyst Circle governance council and is leading a revitalization of Sociocracy for All’s @work circle. Prior to launching Photrek, Nelson was a Research Professor with Boston University Electrical & Computer Engineering (2014-2019) and Sr. Principal Systems Engineer with Raytheon Company (2007-2019). He has pioneered novel approaches to measuring and fusing information. His nonlinear statistical coupling methods have been used to improve the accuracy and robustness of radar signal processing, sensor fusion, and machine learning algorithms. His education in electrical engineering includes a B.S. degree Summa Cum Laude from Tulane University, a M.S. degree from Rensselaer Polytechnic Institute, and a Ph.D. degree from Boston University. His management education includes an Executive Certificate from MIT Sloan and participation in NSF’s I-Corp.
https://www.linkedin.com/in/kenric-nelson-ph-d-7495b77/
M. Sc. Igor Oliveira serves as an algorithm developer, scientist and collaborative partner at Photrek conducting research in complex systems, socioeconophysics, machine learning, quantum computing, and evolutionary dynamics. He graduated summa cum laude with a Bachelor of Science in Materials Physics and also has a Master of science in Physics. Igor served as community teaching assistant for the MITx course 6.86x: Machine Learning with Python for having exceptional performance. His team won Brazil's first quantum computing hackathon by IBM and Itaú Unibanco to solve a portfolio optimization problem. He co-founded the first Society of Physics Students (SPS) chapter in Latin America, promoting outreach events that bridged physics research and community engagement.
https://www.linkedin.com/in/igorgibernoot/
Eystein Magnus Hansen works as a contractor to Photrek through his company North Block AS. Eystein has a master degree in Law and a master degree in Psychology. In the Cardano ecosystem he has been involved primarily in governance and infrastructure work in the last few years. He has worked on topics such as drafting on the Cardano constitution, work at Intersect in various committees such as the Civics committee, and been a Constitutional Committee in Intersect and in the future in Tingvard. On the infrastructure side he has worked as a Staking Pool Operator for several years. For this project he will be assisting on infrastructure and leverage his understanding of the governance side of treasury systems on Cardano.
https://www.linkedin.com/in/eystein-hansen-93376756/
Barry Varys is researcher at Photrek with expertise in the governance of decentralized communities and blockchain systems.
https://www.linkedin.com/in/barryvarys/
Juana Attieh Management Engineer from the University of Waterloo. Juana Attieh is the Product Impact Lead at Photrek.io and co-founder and Chief Strategy Officer at AMLOK.tech. She served as an advisory board member and board observer at intersectmbo.org. Juana co-founded the Cardano MENA community and Off-chain Toronto, as well as LALKUL, Cardano's first team-based DREP committed to exceptional representation in Cardano Governance.
Passionate about decentralized societies, believes in the power of community-led infrastructures, governance, and culture.
Develops projects in decentralized communities.
www.linkedin.com/in/juanaattieh
Megan Hess, Treasurer & Benefits Officer at Photrek, Inc. With 5+ years of experience in the Cardano ecosystem, Megan has led initiatives for startups like Wada and DIT in Cameroon, as well as managing a family farm in Cameroon. Currently, she serves as Vice Chair on Intersect’s Budget Committee. Megan first collaborated with Photrek on their F4 Catalyst project, "Diversifying Voting Influence," and has been selected to lead the Photrek Cardano Circle, where she is committed to driving innovation and supporting decentralized governance and risk intelligence. With a Bachelor’s degree in Physics from the University of Denver and a background in teaching math and physics, Megan excels in communication, team facilitation, and applying sociocratic principles to her management style. Living between the US and Cameroon for the past 6 years with her family, Megan brings a global perspective and a commitment to driving innovation in decentralized governance for the Cardano ecosystem.