Can you automate any trading style?

In practice: yes, as long as the logic can be defined as rules (or a validated model) with clear inputs and execution assumptions. If a strategy relies on truly subjective decisions, we first turn those decisions into explicit criteria you can test and audit.

Do you build the full source code?

Yes. We deliver production-ready code in MT5 (MQL5), TradingView (Pine Script), Python, and C++ — plus documentation and a repeatable testing process. Source ownership is agreed up-front.

Do you provide trading signals or manage money?

No. We build trading software and research tooling. We do not provide investment advice, manage accounts, or guarantee performance.

How do you make sure the bot matches my manual strategy?

Our process is "audit-first": we convert your idea into a document specification, implement with per-trade rule tagging, then iterate using annotated chart screenshots until rule-parity is reached under the agreed assumptions.

Can you backtest on tick data?

Yes. Where it matters, we use tick-level testing and explicitly document assumptions like spread, slippage, commissions, and session rules. We also provide faster iteration runs during development.

Audit‑first strategy automation

Turn your trading idea into an automated strategy you can audit — trade by trade.

We build the full code (MT5, Pine Script, C++, Python), backtest fast on high‑resolution data, and add AI/ML only when it's justified by validation — not hype.

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What you'll get

• A signed Word spec (rules + edge cases + test cases)
• Audited backtests with "why this trade?" evidence
• Production code + deployment + handover

Platforms

• MT5 (MQL5) Expert Advisors
• TradingView (Pine Script) indicators/strategies
• Python + C++ research & performance modules

Rule‑parity

Core promise

Your rules → spec → auditable trades

25+ years

Engineering

Professional software delivery

AI/ML

Optional

When validation supports it

About John Lazar: Toptal Verified Expert (listed on their trading software pages), Stanford SCPD AI/ML teaching experience, and institutional + crypto/DeFi engineering background.LinkedIn · Toptal MT5 · Toptal Trading Software

Services

From strategy notes to production automation

Most automation projects fail because the rules are ambiguous. Our process converts your idea into a spec, then into code with audit logs so you can verify every decision.

Strategy extraction & specification

We extract rules from documents, screenshots, and chat exports — then produce a structured document specification (entries, exits, filters, parameters, and edge cases) you can sign off.

See the workflow

High‑fidelity backtesting & audit

We run realistic backtests and produce trade-by-trade evidence: which rule triggered, what data was used, and what risk constraints applied. You get both fast iteration runs and "gold" report runs.

Backtesting approach

Production code (MT5 / Pine / Python / C++)

Clean, documented, versioned code — with guardrails (max risk, session filters, kill switches) and a deployment checklist. We can also build supporting tools and dashboards.

Service tiers & pricing

AI/ML add‑ons (optional)

Adaptive parameters, signal filters, and custom indicator design — only with time‑series safe validation (walk‑forward, out‑of‑sample, leakage checks) and a monitoring plan.

When ML makes sense

How it works

A workflow traders trust

You should never have to "just believe" a backtest. We make every decision inspectable and iterate until your strategy matches the agreed rules.

1
Intake (notes, screenshots, chat exports)
Send whatever you have — PDFs, TradingView screenshots, Telegram/WhatsApp exports, or a screen recording walkthrough.
2
document specification (single source of truth)
We produce a structured spec: entries, exits, filters, parameters, edge cases, and test cases. You approve before full build.
3
Instrumented implementation
We build the strategy with logging that records exactly which rules triggered and why trades were blocked.
4
Backtest + trade audit report
We generate backtest results with clear assumptions (spread/slippage/commissions) and trade-by-trade evidence.
5
Screenshot feedback loop
You review key moments on the chart, annotate exceptions, and we iterate until rule-parity is achieved.
6
Secure deployment + handover
Deploy behind Cloudflare Zero Trust if needed, provide documentation, and hand over the source with a release checklist.

Have a strategy in screenshots or a chat log?

That's normal. We specialise in extracting messy human logic and converting it into rules that can be tested and automated.

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Proof

Case studies

See how we turn discretionary trading ideas into auditable, automated strategies — with full transparency on metrics, methodology, and assumptions.

View all

Rule‑Parity Automation for a Discretionary Breakout Strategy

MT5 Expert Advisor with trade‑by‑trade audit overlays and risk guardrails.

MT5 (MQL5)Tick backtesting

Read case study

TradingView Indicator + Alert Pipeline for Signal Consistency

Pine Script indicator designed for non‑repainting signals and clean alert logic.

TradingView (Pine Script)Optional webhook integration

Read case study

ML Signal Filter Prototype for Regime‑Aware Strategies

Python research harness for feature design, walk‑forward validation, and model monitoring.

PythonResearch + backtesting

Read case study

FAQ

Common questions

We're engineering-focused and transparent about assumptions, limitations, and what can (and can't) be guaranteed.

Ready to automate your strategy?

Send your notes, screenshots, or chat exports. We'll turn them into a structured specification and an auditable backtest plan.

Book a call Get a quote

Risk disclaimer: Backtests are hypothetical and depend on data quality and assumptions. We build software and research tooling — not investment advice. See risk disclaimer.