Research-minded users
People building watchlists, comparing signals, tracking thesis quality, and learning from paper outcomes.
Research Workstation
SentraCore
A play-money trading research workstation for watchlists, delayed disclosure context, AI-assisted recommendations, paper simulation, manual approvals, and risk review.
Technical Summary
SentraCore at a glance
- Product type
- Market research and paper-trading workstation
- Status
- Working local prototype with seeded research integrations
- Technology stack
- .NET 8, Blazor, ASP.NET Core, EF Core, SQLite, and Serilog
- Architecture
- Layered Web, Domain, Application, Data, Infrastructure, Integrations, and AI projects
- Intended users
- Research-minded individual investors, builders, and analysts
- Safety model
- Paper-only execution, manual approval states, diagnostics, and a hard-disabled live-trading gate
Why it exists
Research before execution
SentraCore is built around the idea that market decisions should move through structure: organize symbols, compare signal sources, review delayed disclosure context, simulate ideas with play money, and only then decide whether anything deserves further attention.
Product Fit
Built for patient research, not impulse trading
SentraCore is meant for users who want a structured place to collect market ideas, review signal context, and practice decision-making before money is involved. The product direction is intentionally slower than a trading terminal: fewer dopamine buttons, more review points.
Solo builders and analysts
Users who want a compact workstation without a heavy institutional trading stack.
Autopilot trading
SentraCore should not imply live auto-trading, guaranteed returns, or AI decision authority.
Hot-tip behavior
Disclosure context and signal cards are prompts for review, not reasons to chase a trade.
Core Workflow
How it works
Track symbols
Create focused watchlists for portfolios, themes, earnings candidates, or high-risk ideas.
Review market inputs
Compare quote freshness, trend sources, disclosure context, and seeded news-analysis inputs.
Generate recommendations
Turn research inputs into traceable recommendation cards with thesis, confidence, and risk context.
Simulate first
Move ideas into Paper Lab, clone plans, mark outcomes, and compare virtual performance.
Review approvals
Approve, reject, or simulate queue items manually while risk guardrails keep pressure on.
Keep an audit trail
Retain approval states, paper activity, price marks, review notes, and diagnostics for later review.
Research inputsWatchlists · market data · news · disclosures
Application servicesRules · recommendations · approvals
Local dataEF Core · SQLite · audit history
Paper workflowSimulation · review · diagnostics
Capability Boundaries
What is working, seeded, and planned
Local application workflows
Watchlist management, Paper Lab experiments, manual queue states, local settings, diagnostics, backups, and review history use real application and EF Core services.
Research intelligence
Disclosure comparisons, example quotes, signal context, recommendation cards, and news-analysis records currently use local fixtures or prototype adapters.
External providers
Live market/news providers and brokerage-adjacent integrations remain behind replaceable contracts, readiness checks, and explicit safety gates.
Live trading
The application’s trading safety gate rejects real order creation. No live brokerage execution is claimed or enabled in this build.
Modules
A compact research stack
Dashboard
Portfolio snapshot, focus ticker chart, trend sources, AI cards, risk guardrails, and queue status.
Watchlists
Symbol groups organized by strategy, theme, portfolio, risk profile, or disclosure overlap.
Market Actors
Delayed public disclosure comparison against watched tickers for research prompts.
Paper Lab
Virtual baskets, cloned ideas, marks, outcomes, confidence, and repeat/watch/avoid decisions.
Settings
Provider assumptions, export behavior, backup expectations, and safety options for future integration work.
Diagnostics
Environment, database, quote freshness, API route, migration, and brokerage lock checks.
Wiki
Built-in guidance for daily workflow, approval rules, terms, and safe first-session habits.
Build Status
Prototype with a clear safety boundary
Review the screensResearch workstation prototype
Dashboard, watchlists, market-actor context, Paper Lab, diagnostics, and wiki guidance are represented in the current build.
Decision journal and review history
The strongest next product step is turning paper decisions into a searchable learning record with outcomes and notes.
Provider integrations behind locks
Quotes, disclosures, and brokerage-adjacent integrations should stay behind readiness checks and manual approval gates.
Screenshots
Built around a safer research loop
SentraCore is designed to slow down risky trading decisions by organizing each idea through watchlists, source context, paper simulation, approval review, and system health checks.
One place for every signal
The dashboard gives users one place to review trade ideas, source quality, chart context, pending approvals, and safety limits before moving deeper into research or simulation.
Research lists with a purpose
Watchlists turn scattered tickers into focused research groups that drive comparison, prioritization, actor-disclosure review, and paper-trading experiments.
Context before confidence
Market Actors helps users identify possible disclosure overlap while keeping the product honest about timing, source delay, and decision risk.
Paper trading before approval
Paper Lab turns an idea into a tracked simulation with virtual positions, marks, review notes, outcome status, and a repeat/watch/avoid decision.
Trust the system state first
Diagnostics makes system health visible so users can slow down when data is stale, provider state is unclear, or safety boundaries are locked.
Guidance built into the product
The wiki documents safe usage, module purpose, daily workflow, approval rules, and shared terminology without forcing users out of the app.
