WizGPT Acceptance Pipeline

Product Features Strategy Builder
1

WizGPT Acceptance Pipeline: Ship Only Policy-Passed Strategies to Paper or Live

Advisors often have many strategy commits to review.

The challenge is not just reviewing code quickly. The real challenge is making sure every strategy is valid, tested, risk-aware, and ready before it moves toward paper trading or live deployment.

That is why Wizzer built the WizGPT Acceptance Pipeline.

With this workflow, advisors can define clear acceptance criteria for what counts as a valid, tested, and deployable strategy. Every time a strategy is committed, WizGPT checks it automatically across logic, risk, guardrails, backtests, and policy rules.

Only strategies that pass both code checks and backtest checks move forward.

This helps advisors maintain quality, reduce manual review effort, and ensure that strategies are promoted only when they meet defined standards.

What the Acceptance Pipeline Does

The WizGPT Acceptance Pipeline acts like a structured review layer for every strategy commit.

It checks the strategy step by step before allowing it to move forward.

The pipeline includes:

  • Policy model

  • Static pre-check

  • Backtest slice

  • Metrics evaluation

  • Policy evaluation

  • WizGPT feedback

  • Iteration loop

  • Promotion gate

  • Audit trail

Think of it as a conveyor belt where strategies are checked, tested, explained, repaired, and promoted only when they pass.

Start With an Advisor Policy Model

The process begins with the advisor creating an acceptance model on Wizzer.

WizGPT can suggest guardrails such as:

  • Code validation

  • Signal logic checks

  • Risk controls

  • Backtest thresholds

  • Compliance checks

  • Kill switch settings

The advisor then defines the acceptance criteria.

This can include entry and exit rules, risk limits, performance thresholds, compliance rules, margin constraints, and deployment guardrails.

Once saved, the model is versioned and listed, ready to guide every strategy downstream.

Policy Models Are Versioned and Auditable

Every advisor can maintain a policy model.

This model may be structured as JSON, OPA/Rego-style rules, or another clearly defined policy format.

Policies can also carry tags such as:

  • Conservative

  • Intraday

  • Options

  • High-risk

  • Low-risk

  • Client-specific

Everything is versioned.
Everything is auditable.

This gives advisors a clear governance layer for deciding which strategies can move forward.

Static Pre-Checks Before Backtesting

Before a backtest runs, Wizzer checks the strategy code structurally.

The strategy code is parsed into an abstract syntax tree or control flow graph. This helps the system inspect the structure of the code before execution.

Wizzer then checks for risky or disallowed patterns such as:

  • Look-ahead bias

  • Martingale or averaging-down logic

  • Missing stop-loss or take-profit rules

  • Leverage cap violations

  • Time-of-day gate issues

  • Hygiene and reproducibility issues

  • Prohibited API calls

  • Unsafe execution patterns

If unsafe patterns are found, the strategy is flagged before it reaches the backtest stage.

This gives advisors a safety filter before any execution-level testing begins.

Backtest Slice and Metrics Evaluation

After the static checks, the strategy moves into backtest evaluation.

Wizzer collects a full evaluation vector across key strategy metrics.

This may include:

  • Drawdown

  • Turnover

  • Heat

  • Slippage

  • Borrow costs

  • Latency

  • Compliance flags

  • Margin usage

  • Exposure

  • Symbol concentration

  • Gap risk

The policy evaluator then applies deterministic thresholds such as maximum drawdown, daily loss, gross leverage, margin limits, symbol weights, correlation rules, and other advisor-defined constraints.

The result is simple:

Pass or fail.

WizGPT Turns Findings Into Actionable Feedback

This is where WizGPT becomes both an analysis engine and a repair assistant.

Using the advisor’s policy, static findings, metric results, exact code spans, and triggered rules, WizGPT produces structured feedback.

Each issue includes:

  • Rule ID

  • Severity

  • Exact code location

  • Why the issue matters

  • Suggested fix

  • Minimal patch, where applicable

Instead of vague warnings, WizGPT provides specific, actionable guidance.

For example, if a strategy has no stop-loss defined for a sell leg, WizGPT can identify the exact file and line range, explain why it matters, and suggest a minimal fix such as adding a stop-market order within the advisor’s risk policy.

This makes strategy iteration faster, safer, and more consistent.

The Strategy Review Loop

The acceptance pipeline works as a continuous loop:

Commit → Pre-check → Backtest → Policy evaluation → WizGPT feedback → Revise → Recommit

Only when the strategy reaches a policy pass can it be promoted to paper trading or live deployment.

If the strategy fails, WizGPT explains the issues and provides suggestions to bring it closer to the acceptance criteria.

This creates a clean review workflow where strategy builders can improve systematically instead of relying on manual guesswork.

Static Lints as the First Safety Filter

Static lints help identify structural risks before the strategy is executed.

The code is scanned for patterns such as:

  • Missing stop or limit orders

  • Martingale or averaging-down behavior

  • Time-of-day gate issues

  • Improper parameter bounds

  • Prohibited calls such as time.sleep or raw sockets

  • Unsafe sizing logic

  • Missing risk controls

If a violation is detected, a red-flag node is raised with the exact file and line span.

That branch is blocked from moving forward until it is fixed.

If no violations are found, the strategy is marked clean and allowed to proceed to backtesting.

Metrics Lints After the Backtest

Once the backtest outputs are available, Wizzer runs metric-based checks.

These include threshold checks for:

  • Drawdown

  • Daily loss

  • Leverage

  • Margin

  • Exposure

  • Weekend or overnight holding

  • Borrow fees

  • Slippage

  • Gap risk

Wizzer can also run statistical smell tests for:

  • Concentration risk

  • Regime overfit

  • Trade clustering

  • Path dependence

  • Multiple hypothesis risk

Together, static lints and metrics lints create a deterministic safety net before a strategy can move forward.

Governance and Audit Trail

At every step, governance rules apply.

Only authorized roles can promote strategies.

Every action is logged as part of the audit trail, including commits, checks, feedback, fixes, backtest results, and promotion decisions.

This helps advisors maintain control as their strategy review workflow scales.

No Engine Fork Required

The acceptance system does not require changing the core trading engine.

Instead, it can listen through a custom result handler, collect outputs from runs, and add acceptance status in parallel.

A lightweight Wizzer runner connects to the strategy engine and shares results with both the engine and the acceptance pipeline.

This allows checks and gating to happen without disrupting the core execution workflow.

Example Rule: Disallow Averaging Down

One example rule is to disallow averaging down.

The static detector can identify when position size increases while unrealized P&L is negative.

WizGPT can then generate feedback such as:

  • The strategy increases size while the trade is losing

  • This violates the selected risk policy

  • Replace additive sizing with volatility-scaled entries

  • Bound position size by risk per trade

  • Apply the attached patch and rerun checks

This turns policy enforcement into practical guidance that the strategy builder can apply immediately.

Why This Matters for Advisors

The WizGPT Acceptance Pipeline helps advisors review more strategies with stronger consistency.

It supports:

  • Faster strategy review

  • Clear acceptance criteria

  • Automated guardrail checks

  • Backtest-based validation

  • Policy-driven promotion

  • Role-based governance

  • Audit-ready decision history

  • Actionable repair guidance

For advisors managing multiple strategy builders, this creates a structured way to ensure that only policy-passed strategies move to paper or live environments.

Turn On WizGPT Acceptance for Your Strategies

Acceptance you can trust.
Guidance you can apply.

Turn on WizGPT Acceptance from Settings → Compliance & QA.

Start with your policy, run pre-checks, review WizGPT feedback, and ship only policy-passed strategies to paper or live.

Sign up on Wizzer today and build advisor-grade strategy governance into your workflow.

For queries or support, contact us on WhatsApp: +91 8928065586