Apakah teknologi yang diklaim sebuah perusahaan benar-benar nyata? DDE membaca basis kode untuk memverifikasi klaim teknis serta menangkap kepalsuan dan AI-washing — lalu membandingkannya dengan industri dan pesaing dan menilai kelemahan Anda sendiri, semuanya dari IDE Anda.
+ Parallel Atlas 4-Axis (35% Crypto Core)
+ 30-Item × 10-Co. Capability Matrix
With Data Provenance Box & Source Appendix
Runs inside your existing IDE AI subscription
Due Diligence Engine (DDE) adalah perangkat baris perintah open-source yang mengubah agen AI di IDE Anda — Claude Code, OpenAI Codex CLI, Google Gemini CLI, Antigravity, Cursor, GitHub Copilot — didukung Claude Opus 5.5 / Sonnet 5.5, Gemini 4 Argon, GPT-5, dan lainnya — menjadi analis teknis kelas dunia. Ia membaca seluruh basis kode dari target mana pun — perusahaan portofolio, target akuisisi, pesaing, atau tim Anda sendiri — memverifikasi apakah teknologi yang diklaim benar-benar diimplementasikan, meneliti pasar dan pesaing secara langsung, serta menilai kekuatan dan kelemahan di berbagai dimensi berbobot menjadi laporan PDF bernilai konsultasi di folder Downloads Anda. Semuanya berjalan secara lokal di dalam sandbox AI IDE Anda — tanpa API key, server pihak ketiga, telemetri, atau biaya tambahan.
Generic AI code reviewers stop at checkbox compliance ('Has auth? ✓ Has HTTPS? ✓'). DDE inspects actual cryptographic primitives (Signal Protocol, PQXDH + ML-KEM-1024, libsignal/BoringSSL FFI vs. self-rolled crypto), concurrency models, and live 2026 market sources.
Eliminates stale training-cutoff analysis. Before inspecting the repo, the agent searches 2026 competitor acquisitions, shutdowns, funding rounds, CVEs, and regulatory shifts. Every matrix cell carries source URLs + verification dates, surfaced in the PDF Data Provenance Box.
"data_freshness": {
"web_search_performed": true,
"search_date": "2026-10-22",
"queries_executed": 14,
"sources_cited": 28
}In v0.6.2, heuristic false positives (git rebase timestamp diffs, high-velocity commits, documentation buzzword counts) are silently discarded and blocked by _filter_red_flags. Only genuine code-level security gaps, race conditions, and logic bugs with exact file:line and fix plans appear.
{
"severity": "HIGH",
"file_path": "src/crypto/session.rs:142",
"title": "Nonce reuse risk on concurrent retry",
"description": "Use atomic counter or ChaCha20Poly1305 random nonce..."
}Third-party badges (SOC2, ISO, HIPAA) are reference-only and never scored. DDE audits 4 claim-vs-code consistency checks plus 6 code-measured capabilities: Cryptographic depth, Concurrency model, I/O patterns, Caching architecture, Scalability, and ML implementation depth.
Claim vs Code (4): Pitch accuracy / Feature completeness
Code Measured (6): Crypto FFI / Concurrency / I/O / Cache / Scale / MLSetiap pitch deck mengaku "bertenaga AI." Hanya sedikit yang bisa membuktikannya. Uji tuntas teknis itu lambat, mahal, dan sulit diskalakan di sepanjang pipeline.
Bahasa pemasaran melebih-lebihkan — atau bahkan mengarang — kemampuan yang sebenarnya tidak didukung oleh basis kode. Menemukan celah itu menyita waktu seorang insinyur senior.
Membaca basis kode, memetakan arsitektur, dan membandingkan pesaing untuk setiap kesepakatan menghabiskan waktu kerja ahli berhari-hari yang jarang Anda miliki.
Tanpa dasar teknis yang objektif, keputusan harga dan risiko bersandar pada narasi founder, bukan pada bukti.
Every report delivers both the balanced 5-Dimension Standard Score (equal 20% weights) and the parallel Atlas 4-Axis Engineering Philosophy (55% weighted toward deep cybersecurity engineering).
API Wrapper vs. Genuine IP
Distinguishes thin third-party API wrappers from defensible proprietary algorithms, protocols, and custom engineering.
Stack Modernity & Cryptographic Edge
Evaluates 2026-grade language safety, runtime efficiency, post-quantum primitives (ML-KEM-1024), and modern toolchain maturity.
PoC Demo vs. Production Grade
Inspects error handling, edge cases, migrations, state machines, and automated test coverage to separate demos from production code.
Structural Integrity + Integrated Security (v0.3)
Evaluates security posture as an inseparable foundation of production architecture alongside modularity, fault isolation, and scalability.
Pitch Deck & Website Claims vs. Code Reality
Cross-examines public marketing claims ('AI-powered', 'E2EE', 'Zero-Knowledge') against actual repository implementation to expose AI-washing.
Strong investment candidate
Viable with conditions
Significant concerns
High risk
Do not invest (or Critical Deal-Breaker)
Generates 7 consulting frameworks across 6 global regions, plus an 8th chart: a ~30-item × 5–10 competitor Implementation Capability Matrix dynamically tailored to the target's industry with 3–5 line competitor selection rationales.
Vision × Execution
Market Growth × Relative Share
Competitive Position × Technical Moat Depth
Security Implementation × Privacy Readiness
Data Protection × Audit Transparency
Downside Risk × Upside Potential
R&D Velocity × ARR Traction (3D Bubble)
Uses the 4-state Japanese tech rating standard (○ / △ / × / ?) with primary source URLs and verification dates on every cell.
Publicly documented & verified in code, whitepapers, or specs
Asserted in marketing, but not independently verifiable
Explicitly absent in documentation or architecture
Cannot be determined from public evidence (preferred over guessing)
| Category / Capability | Target | Comp. A | Comp. B | Comp. C | Provenance (sources + last_verified) |
|---|---|---|---|---|---|
Core Cryptography Hybrid Post-Quantum Key Agreement (PQXDH / ML-KEM-1024) | ○ | ○ | × | △ | [2026-10-22] Verified FIPS 203 ML-KEM-1024 + X25519 FFI implementation |
Metadata Privacy Sealed Sender / Zero-Knowledge Routing | ○ | ○ | × | × | [2026-10-22] Verified sender certificate encapsulation across relays |
Data Governance Cryptographic Message Retirement (Tombstone Zeroize) | ○ | △ | × | ? | [2026-10-22] Verified Ed25519-signed Tombstone & cache zeroization |
Audit Transparency Public Source Code & Automated Security CI | ○ | ○ | × | × | [2026-10-22] Verified public GitHub repository & CodeQL/osv-scanner CI |
* In live PDF reports, the ~30 capability items and 5–10 top competitors are dynamically selected for the target's industry (Messaging, Fintech, Medical, Gaming, SaaS, IoT), with all cited URLs listed in the Source Appendix.
Typeset in black and Atlas Blue (#5271FF), combining executive synthesis, code-level evidence, global market charts, and a cryptographic purge certificate (~22–24 pages depending on findings).
5-dim horizontal bars, 5-dim radar chart, Data Provenance Box (search date, query & source counts, or training-cutoff warning), and business + technical synthesis.
Evidence-backed SWOT grid, per-dimension enablers, 1/3/5-year projections with confidence, immediate/medium/long-term roadmap, and investment thesis.
Genuine code defects only (file:line + fix plan) and the 10-item technical audit (4 claim-vs-code + 6 code-measured).
Regional positioning charts, 3–5 line rationale per competitor (HQ, market position, why chosen), and the ○△×? capability matrix.
Performance / Stability / Lightweight / Security Strength bars plus a plain-language executive glossary (MFA, SOC2, libsignal, PQXDH).
Engineering rebuild time/cost estimation, complete URL Source Appendix (added in v0.6.0), and cryptographic workspace purge certificate.
Penilaian teknis yang berulang dan mengutamakan bukti — rubrik yang sama untuk setiap kesepakatan.
Membandingkan pitch dengan basis kode yang sebenarnya untuk memastikan apa yang benar-benar dibangun versus apa yang sekadar diklaim.
Menandai di mana "AI" hanyalah pembungkus tipis, heuristik yang di-hardcode, atau sama sekali tidak ada — memisahkan ML sejati dari sekadar pemasaran.
Menghasilkan skor 0–100 dan nilai huruf di berbagai dimensi dengan bobot setara, disertai alur penalarannya.
Memetakan struktur, dependensi, dan pilihan desain untuk menilai kemudahan pemeliharaan, skalabilitas, dan utang teknis.
Meneliti pesaing nyata, pendanaan, dan informasi keamanan di web lalu menyusun perbandingan pasar yang bersumber jelas.
Berjalan sepenuhnya di dalam sandbox AI IDE Anda. Tanpa server pihak ketiga, tanpa telemetri — diaudit dengan CodeQL, Dependabot, dan pip-audit.
DDE itself operates zero third-party servers and zero telemetry. Choose the exact execution boundary that matches your security policy.
$ dde prompt --pdfDDE locally generates a structured prompt. Code reading and PDF generation happen inside your existing IDE AI agent session (Claude Code, Codex, Gemini CLI, Antigravity, Copilot, Cursor).
DDE makes zero outbound calls. Your AI agent runs STEP 0 live web searches for public competitor & CVE data.
$ dde analyze . --skip-aiSource code is analyzed 100% locally in memory/temp workspace and never sent to any AI model or external service.
In v0.6.3 (780e3cd / aac4c77), --skip-ai strictly disables API key auto-loading and blocks all outbound network requests.
$ dde analyze owner/repoUses your own API keys to cross-verify across up to 3 providers via the unified SSOT registry (BYOK_DEFAULT_MODELS / PROVIDER_MODEL_COSTS): Anthropic (Claude Haiku 5.5 → Sonnet 5.5 → Fable 5.1), Google (Gemini 4 Argon), and OpenAI (Astra gpt-6.1-sol / GPT-5).
Configured for zero-retention API endpoints (store=False, with fail-closed enforcement on GoogleProvider). Strips user:token@ credentials from GitHub URLs and immediately dereferences PATs after single in-memory use.
Eradicated all 36 audit defects across 35+ modules with GPT-6-Astra (xhigh) & Gemini 4 Argon, unified the SSOT model/cost registry, and locked permanent verification with 156 automated tests (tests/test_audit_regressions.py + tests/test_zero_drift_invariants.py).
Blocks Zip Slip traversal, symlinks, and FIFO special files during archive ingestion, and strips user:token@ credentials from GitHub URLs. Preserves .git during analysis for commit forensics, then performs in-place "r+b" 3-pass zero-fill shredding with strict os.walk(onerror=...) failure propagation and Windows NTFS user-only ACL locking.
Site verification (site_analyzer.py) enforces ip.is_global to block RFC 6598 CGNAT (100.64.0.0/10), private, loopback, and cloud metadata IPs as well as unsafe redirects, using reentrant DNS pinning (_pinned_dns_context) to prevent time-of-check to time-of-use (TOCTOU) DNS rebinding attacks.
Applies _esc_text across all dynamic PDF fields (ImplementationMatrix, sources, RedFlags) to prevent ReportLab XML parser crashes. Protects Latin digits and ASCII punctuation with Helvetica in Arabic (ar) and Thai (th) to prevent missing-glyph tofu boxes (□) across 24-page PDFs, enforces Jinja2 autoescape=True, and guarantees idempotent Score.compute().
Unifies __version__, BYOK_DEFAULT_MODELS, and PROVIDER_MODEL_COSTS (Astra gpt-6.1-sol $2/$10, gpt-6-astra $5/$25, gpt-5 $1.25/$10, Haiku >100k tiered rate) in config.py SSOT. Enforces fail-closed store=False on GoogleProvider, supports async def AST analysis, and locks 156 CI tests via test_zero_drift_invariants.py.
DDE menghasilkan prompt terstruktur yang dapat dieksekusi oleh agen AI mana pun yang mampu membaca file dan menjalankan shell. Tanpa plugin khusus DDE atau login.
Instal dari repositori publik dengan satu perintah pip. Python lokal murni — tanpa akun, tanpa konfigurasi.
Dari proyek target, jalankan perintah DDE di terminal AI IDE Anda. Langganan AI yang sudah Anda miliki yang melakukan analisis — tanpa biaya tambahan.
Agen membaca ratusan file, mengevaluasi di berbagai dimensi berbobot, serta meneliti pesaing, pendanaan, dan informasi keamanan secara langsung di web.
PDF bergaya konsultasi mendarat di folder Downloads Anda — dengan skor 0–100, nilai huruf, lanskap kompetitif, dan dasar pemikiran yang bersumber jelas.
New in v0.6.3: paste Method A directly into your AI agent chat for fully automated install + audit + PDF generation, or run Method B in your terminal. Bundled Noto fonts render 14 PDF languages out of the box.
✓ Your current locale is natively supported for localized PDF output (14 languages).
Install https://github.com/Atlas-Associates-Inc/Due-diligence-engine (python3 -m pip install -U --no-cache-dir git+https://github.com/Atlas-Associates-Inc/Due-diligence-engine.git), run dde prompt --pdf --lang id on this project, and execute the entire generated prompt (STEP 0 live web research, full code audit, JSON generation, and PDF rendering) end-to-end to save the consulting PDF report to ~/Downloads/.python3 -m pip install -U --no-cache-dir git+https://github.com/Atlas-Associates-Inc/Due-diligence-engine.git && dde prompt --pdf --lang iddde doctordde prompt --pdf --lang id --url https://example.comWorks out of the box in any AI agent capable of reading files and running shell commands.
Boutique consulting depth with local-first privacy at zero added software cost.
| Dimension | DDE (v0.6.3) | Manual DD Consulting | Generic AI Code Review | SaaS DD Platforms |
|---|---|---|---|---|
| Added Cost | $0 (uses your IDE AI) | $$$$ (consultant fees) | Per-token API fees | $$$$ (enterprise subscription) |
| Code Privacy | Local / IDE sandbox (0 DDE servers) | Manual NDA & repo sharing | Uploads code to vendor | Stores code in vendor cloud |
| Deliverable | 24-page consulting PDF (14 langs) | Bespoke report | Inline PR comments | Web dashboard |
| Data Freshness | Live web search (2026) + URLs | Depends on analyst | Training cutoff only (stale) | Vendor refresh cycle |
| Crypto & Security Depth | PQXDH / ML-KEM-1024 / FFI audit | Depends on consultant | Surface checklist | Surface checklist |
| Competitive Benchmarks | 7 charts × 6 markets + 30-item matrix | Manual research (weeks) | None | Limited |
| Red Flag Precision | Code-verified only (file:line + fix) | High (slow) | High false-positive noise | Heuristic rule noise |
| Setup & Turnaround | 1 command / ~10–20 min | 2–4 weeks | Minutes (partial) | Days (onboarding) |
Entah Anda sedang mengambil keputusan investasi, menilai rekayasa Anda sendiri secara objektif, atau membandingkan pesaing — bukti dari kode, dengan cepat.
VC, dana pertumbuhan, dan tim M&A: saring risiko teknis dan kebenaran di balik klaim di sepanjang pipeline Anda sebelum penelaahan mendalam.
Jalankan DDE pada basis kode Anda sendiri untuk melihat kekuatan, kelemahan, dan utang teknis melalui sudut pandang pihak ketiga — guna memprioritaskan perbaikan atau bersiap menghadapi penggalangan dana.
Bandingkan tumpukan teknologi dan kedalaman implementasi pesaing dari repositori publik dan data pasar, lalu pahami posisi Anda sendiri dengan bukti.
Ya. DDE bersifat open source di bawah lisensi Apache 2.0. Ia menggunakan langganan AI yang sudah Anda miliki di IDE, sehingga tidak ada API key dan tidak ada biaya tambahan.
Tidak. DDE adalah Python yang 100% lokal dan berjalan di dalam sandbox AI IDE Anda. Tidak ada server DDE dan tidak ada telemetri. Riset web hanya mengambil informasi publik tentang pesaing dan pasar.
Agen apa pun yang dapat membaca file dan menjalankan perintah shell. Telah diverifikasi dengan Claude Code, OpenAI Codex CLI, Google Gemini CLI, Antigravity, dan GitHub Copilot Agent Mode (mendukung model terbaru seperti Claude Opus 5.5 / Sonnet 5.5, Gemini 4 Argon, dan GPT-5), serta bekerja dengan Cursor, Gemini Code Assist, Aider, Windsurf, dan terminal agentik serupa.
PDF bernilai konsultasi (sekitar 24 halaman) yang tersimpan ke folder Downloads Anda, lengkap dengan skor keseluruhan 0–100, nilai huruf, lanskap kompetitif, matriks implementasi, dan dasar pemikiran yang bersumber jelas.
AI-washing adalah memasarkan sebuah produk seolah bertenaga AI padahal teknologi yang mendasarinya minim atau tidak ada. DDE membandingkan klaim dalam pitch dengan implementasi nyata di basis kode lalu menandai celahnya.
Instal sekali, jalankan dari AI IDE mana pun, dan baca sendiri buktinya. Gratis dan open source.