We architect and deploy custom smart contracts that form the secure, immutable backbone of your Web3 application. Our development process is built on audited security patterns and gas-optimized code, ensuring reliability and cost-efficiency from day one.
LABS
Services
Voting Mechanism Simulation & Modeling
Deploy governance with confidence. We use agent-based modeling and economic simulation to stress-test your custom voting algorithms, identifying game theory vulnerabilities and unintended economic outcomes before they go live.
Chainscore © 2026
overview
CORE INFRASTRUCTURE
Custom Smart Contract Development
Secure, production-grade smart contracts built to your exact specifications.
From concept to mainnet, we deliver contracts you can trust for high-value transactions and complex logic.
- Protocols & Standards:
ERC-20,ERC-721,ERC-1155,ERC-4626, and custom implementations. - Security First: Development with
OpenZeppelinlibraries, comprehensive unit testing, and pre-audit readiness. - Deliverables: Full source code, deployment scripts, technical documentation, and a 2-week MVP timeline for standard token contracts.
key-features-cards
QUANTITATIVE VALIDATION
Our Simulation & Modeling Capabilities
We move beyond theoretical design. Our quantitative simulations model real-world voter behavior and network conditions to identify vulnerabilities and optimize for security, fairness, and efficiency before deployment.
01
Sybil Attack Resistance Modeling
Simulate sophisticated Sybil and collusion attacks to quantify the cost-to-attack your mechanism. We provide concrete recommendations for stake-weighting, delegation limits, and identity verification thresholds.
>10 Attack Vectors
Modeled
Cost-to-Attack
Quantified
02
Voter Behavior & Incentive Analysis
Model voter apathy, rational ignorance, and delegation patterns using agent-based simulations. Optimize participation incentives and quorum requirements to ensure governance legitimacy.
Agent-Based
Simulations
Participation Rate
Forecast
03
Gas & Cost Optimization Modeling
Profile gas consumption across voting lifecycle events—from proposal creation to execution. We identify bottlenecks and architect mechanisms for predictable, sub-dollar voting costs at scale.
< $1
Target Cost/Vote
Gas Profiling
Full Lifecycle
04
Parameter Stress Testing
Systematically test voting duration, proposal thresholds, and veto powers under high-load and adversarial conditions. Establish safe operational bounds and fail-safe parameters.
Boundary Analysis
Performed
Fail-Safe Params
Defined
05
Fork & Governance Crisis Simulation
Model contentious vote outcomes and hard fork scenarios. Design dispute resolution mechanisms and treasury management rules that maintain protocol integrity during governance failures.
Crisis Scenarios
Simulated
Contingency Plans
Architected
benefits
MITIGATE CRITICAL RISKS
Why Stress-Test Your Voting Mechanism
Simulated attacks and load testing reveal vulnerabilities before they impact your protocol's security, governance integrity, and token value.
02
Validate Economic Incentives
Model voter behavior under market stress to ensure your tokenomics and reward structures remain robust and aligned with protocol goals.
03
Ensure Scalability Under Load
Test voting throughput and gas costs with thousands of simultaneous participants to guarantee performance during high-engagement governance events.
04
Audit for Regulatory Compliance
Simulate edge cases and on-chain interactions to provide evidence for security audits and demonstrate due diligence to partners and regulators.
A Quantitative Comparison for Governance Protocols
Simulation vs. Traditional Audit
Traditional audits are essential but reactive. Our simulation-driven modeling provides proactive, quantitative validation of your voting mechanism's security and economic resilience under real-world conditions.
| Evaluation Factor | Traditional Audit Only | Chainscore Simulation & Modeling |
|---|---|---|
Attack Vector Discovery | Static analysis of known patterns | Dynamic simulation of novel attack vectors (e.g., whale manipulation, flash loan governance attacks) |
Economic Security Validation | Qualitative assessment | Quantitative stress testing with Monte Carlo simulations |
Voter Behavior Modeling | Not applicable | Agent-based modeling of voter apathy, delegation patterns, and incentive alignment |
Time to Insight | 2-4 weeks post-development | Integrated into development lifecycle; feedback in days |
Cost of Failure Discovery | High (post-deployment exploit) | Low (pre-deployment simulation) |
Quantifiable Output | Vulnerability report | Security score, economic resilience metrics, parameter optimization recommendations |
Team Requirement | Auditor expertise only | Protocol economists, game theorists, and security engineers |
Typical Engagement | $15K - $50K+ | $30K - $100K+ (comprehensive modeling) |
how-we-deliver
METHODOLOGY
Our Modeling Process
A rigorous, four-phase approach to de-risk your governance design. We translate complex tokenomics into actionable, battle-tested models that predict real-world behavior.
01
1. Mechanism Design & Specification
We formalize your governance logic into a precise mathematical model, defining voter incentives, proposal mechanics, and quorum rules. This creates a single source of truth for your protocol's decision-making engine.
2-5 days
Initial Model
100%
Logic Coverage
02
2. Agent-Based Simulation
We simulate thousands of virtual voters with different strategies (rational, malicious, apathetic) to stress-test your mechanism under realistic and adversarial conditions. Identifies Sybil attack vectors and voter apathy risks.
10k+
Agent Scenarios
> 95%
Attack Surface Mapped
03
3. Parameter Optimization
Using Monte Carlo methods, we systematically tune critical parameters (quorum thresholds, voting periods, proposal deposits) to maximize desired outcomes like participation and security while minimizing governance overhead.
50+
Iterations
Optimized
Gas & UX
04
4. Audit-Ready Report & Implementation
Receive a comprehensive report with vulnerability analysis, parameter recommendations, and visualizations. We provide Solidity/Vyper code snippets and specifications ready for your development team or external audit.
Audit-Ready
Deliverables
2-3 weeks
Full Engagement
Technical & Commercial Details
Voting Simulation FAQs
Answers to common questions from CTOs and product leads evaluating our voting simulation and modeling services.
We follow a structured 4-phase engagement: 1) Discovery & Scoping (1 week): We analyze your governance model, tokenomics, and attack vectors. 2) Model Design (1-2 weeks): We build custom simulation models in Python/Go, defining voter cohorts and incentive structures. 3) Simulation & Stress Testing (2-3 weeks): We run thousands of simulations, testing for Sybil attacks, voter apathy, and parameter exploits. 4) Reporting & Integration (1 week): We deliver a detailed findings report and provide integration support for your smart contract team. This phased approach ensures predictable timelines and clear deliverables at each stage.
ENQUIRY
Get In Touch
today.
Our experts will offer a free quote and a 30min call to discuss your project.
NDA Protected
Confidentiality24h Response
Time to ValueDirectly to Engineering Team
No Sales Fluff10+
Protocols Shipped
$20M+
TVL Overall