Productized Fractional-CTO rail

Make AI-assisted coding
enterprise-acceptable.

Five gates wrap every prompt and every output. Full audit trail. Cost ceiling per project. Drift, secret, and citation guards — built so your engineering org can adopt AI without the legal, security, and observability nightmares.

Talk to us

Built by engineers who've shipped inside Fortune-500 enterprises and regulated fintechs.

Designed against the controls real enterprises actually run

SOX-aware audit trail· SOC 2-friendly logging· HIPAA-compatible deploy· FedRAMP airgap mode· BYOK encryption

The contrarian frame

Memory isn't the bottleneck.
Trust is.

Most "AI coding tools" race to fix forgetting. None of them give your CTO an audit trail, a cost ceiling, or a way to know the model didn't drift off-spec last Tuesday. That's why AI-generated code rarely makes it past compliance review.

Five gates

Every prompt and every output, inspected.

G1 audit. G2 prompt-quality. G3 citation. G4 drift. G5 railguard. Five layered checks that your team never has to write themselves — battle-tested, cached, and circuit-breaker-resilient.

  • Heuristic + LLM-judge layered on every pre-prompt
  • Citation grading verifies every cited path actually exists
  • Drift detection on rolling 50-output baseline
  • Secret + path-traversal guards, fail-closed by default
verdicts.live
streaming
G1passscope: ai-coding-rail.allowed_intent42ms
G2passquality 0.83 · refs:3 · verbs:2118ms
G3passcited 4/4 chunks · path-safe76ms
G4softdrift 0.18 · within tolerance12ms
G5passno secrets · no path traversal8ms
composer · approve→ proceed to ship
audit_events · idempotent
last 6 events
Recent audit ledger events written to Postgres and Langfuse — illustrative.
tsgateverdictactorledger
14:02:11G1passmanjeet@#34,221
14:02:12G2passmanjeet@#34,222
14:02:13G3passmanjeet@#34,223
14:02:13G4soft_flagmanjeet@#34,224
14:02:14G5passmanjeet@#34,225
14:02:14·approvecomposer#34,226
dedup_key · ON CONFLICT DO NOTHING→ export audit pack
Audit-friendly by default

A ledger your CTO can actually defend.

Every prompt, every output, every gate verdict — recorded once, idempotently, with a deterministic dedup key. Pull a per-project audit pack on demand for legal, security, or board review.

  • Idempotent writes — safe under retries
  • Dual-write to Postgres + Langfuse
  • Sessions tie multi-turn coding sessions together
  • 12 named scores per pipeline run
Drift, in real time

Know the moment the model wanders off-spec.

Cosine similarity over a rolling 50-output baseline. When tone, scope, or style drifts past tolerance, the rail soft-flags or blocks before bad code lands in your tree.

  • Per-project baseline · tunable threshold
  • Soft-flag → review · hard-flag → block
  • Visible per-prompt in Langfuse
drift_score · last 50 outputs
0.18/ 0.30 threshold
block
0.04
min
0.18
p50
0.27
p99

Live demo · loop

Watch a real run move through the rail.

Every prompt produces a verdict trail, an audit row, and a cost line — in under a second.

~/projects/auksia · main
rail · live
$ claude-code "refactor the rate-limiter to use Redis sorted sets"
▸ rail intercepts prompt
G1 audit ......... pass // scope match: src/rate_limiter/*
G2 quality ....... pass // score 0.84 (verb:2 refs:1)
retrieve ......... 8 chunks // hybrid + rerank
coder ............ drafted // 1.2s · gpt-4o-mini
G3 citation ...... pass // 4/4 chunks cited
G4 drift ......... soft // 0.18 (threshold 0.30)
G5 railguard ..... pass // no secrets · no traversal
▸ approved · ledger #34,226 · cost $0.0007
 
Verdict trail
5 / 5 gates approved
Total cost
$0.0007USD
openai · 1,245 tok
Latency
312ms
p99 over last hour
Audit ledger
#34,226
pg + langfuse · idempotent

The five gates

A station for every concern.

G1pre-prompt

Audit

Stops off-mission prompts before they spend a single token. Filters intent against the project's allowed scope.

G2pre-prompt

Prompt Quality

Catches vague prompts that produce hallucinated code. Heuristic + LLM-judge rescue with branded composer feedback.

G3post-output

Citation

Verifies every file path, function, and symbol the model cites actually exists in your codebase. Path safety + semantic grading.

G4post-output

Drift

Detects output style or scope drifting from a rolling 50-output baseline. Cosine similarity over output embeddings.

G5post-output

Railguard

Blocks secrets, dangerous file writes, and path traversal at the boundary. Pattern + rule layered, fail-closed by default.

When a gate blocks

Branded composer message.

Instead of a cryptic error, the rail returns an LLM-composed explanation injected into your dev's editor — a clear, on-brand reason and a corrective next step.

Integrations · BYOLLM

Plugs into your stack. Locks into none of it.

CTO Rail sits between any AI coding client and any LLM provider — vendor-neutral by design.

AI coding clients
1 live · 4 soon
  • CC
    Claude CodeLive
  • ▶
    CursorSoon
  • »
    Continue.devSoon
  • A
    AiderSoon
  • Z
    Zed AISoon
JSON hook contract · pre/post
LLM providers
1 live · 4 soon
  • A
    Anthropic ClaudeSoon
  • O
    OpenAILive
  • Br
    AWS BedrockSoon
  • Az
    Azure OpenAISoon
  • Ol
    Ollama · vLLMSoon
Per-gate provider routing
Data plane · observability
3 live · 2 soon
  • Pg
    Postgres · SupabaseLive
  • Lf
    Langfuse (self-hosted)Live
  • Rd
    Redis (cache + breaker)Live
  • Gf
    Grafana / DatadogSoon
  • S3
    S3 / GCS audit packsSoon
All inside your perimeter

Side-by-side

Different category.
Different buyer.

Memory plugins help a developer remember. CTO Rail helps an engineering org govern.

Side-by-side comparison: CTO Rail versus raw AI assistants and memory plugins, across eight enterprise capabilities.
Capability
Raw AI
assistant
Memory
plugins
 ★ winner
CTO Rail
this page
Cross-session memory
Audit trail for compliance
Per-project cost ceiling
Drift detection
Citation grading
Secret + path guards
Bring-your-own LLM
 vendor-locked vendor-locked Any provider
Multi-tenant SaaS-ready
 n/a Architected
Score
0/8
1/8
8/8
verdict

Hover a row to see the rail's win light up · architected = on the roadmap, see Integrations.

Principles · how we think

The rules we
built it under.

Six conviction rules. Every decision in CTO Rail traces back to one of them.

01

Fail closed by default.

When a gate is uncertain, the answer is block. Better a developer rephrases than ships un-audited code.

02

Log everything. Idempotent. Forever.

The audit trail is the product. Every prompt, every output, every verdict — written once, deterministically, with a dedup key.

03

Vendor-neutral by construction.

Any LLM. Any data plane. Any IDE. Protocol-based ports. Hooks, not lock-in.

04

Cost is observability.

Every gate verdict ships with its dollars. You can't govern what you can't price.

05

Designed against real controls.

Built for the room nobody invites you to — the SOX audit, the board review, the 2 a.m. compliance call. Against the controls, not around them.

06

No hidden state.

If a gate blocks, the dev sees why, where, and what to fix — composed in plain English, on-brand, in their editor.

— rules I wish I'd had during a decade in enterprise & fintech, MS v0.2 · 2026 · ctorail.com

Telemetry · live

Real numbers
from the rail.

Aggregated across active pilot deployments. The board refreshes on each visit.

live
VERDICTS
PROMPTS TODAY
DRIFT P50
COST TODAY
UPTIME 30D
representative pilot cost in USD · drift p50 ×100 uptime in ‰ (per-mille)
Pilot · Boarding now

A safer future for AI coding
is now boarding.

Book a 30-minute demo. We'll wire CTO Rail against your codebase live, run a prompt through all five gates, and walk you through the audit trail.

Next departures
live
Available pilot engagements: 30-min demo, architecture deep-dive, and 2-week paid pilot.
Service Status
30-min Demo Boarding
Architecture deep-dive Boarding
2-week paid pilot Open · 2 slots
Architecture deep-dive
White-glove onboarding
Pilots from low four-figures / mo
14-day pull-out
ctorail.com Conductor: Manjeet Singh manjeet.singh@aiinfox.com

Contact · let's talk

Reach the
conductor.

Tell us what you're trying to ship safely. We respond within 24 hours.

Direct lines
Email
manjeet.singh@aiinfox.com
Response
Within 24 hours · Mon–Fri
Deployment
Inside your perimeter
self-hosted · BYO cloud · no data leaves
Async chat
Slack Connect available for pilot teams
Common asks
  • · "Show me a live verdict trail on our repo"
  • · "How do you handle Bedrock or Anthropic Claude?"
  • · "What's the audit-pack format?"
  • · "Can we self-host the entire stack?"
Send a note

Tell us about your stack.

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Frequently asked

Common questions.

Short, factual answers — what CTO Rail is, how it deploys, and how it differs from memory plugins and raw AI assistants.

What is CTO Rail?
CTO Rail is an AI policy rail for AI-assisted software engineering. Five gates — audit, prompt-quality, citation, drift, and railguard — wrap every AI prompt and every output, producing a full audit trail, a per-project cost ceiling, and drift, secret, and citation guards. It is built for enterprises and regulated fintechs adopting Claude Code, Cursor, and Copilot.
How does CTO Rail differ from memory plugins?
Memory plugins help an individual developer remember context across sessions. CTO Rail helps an engineering organization govern. It is the only category with cross-session memory plus an audit trail, per-project cost ceiling, drift detection, citation grading, secret and path guards, and bring-your-own-LLM — all designed for compliance review, not personal productivity.
Can I self-host CTO Rail inside my VPC?
Yes. CTO Rail is designed self-hostable by default. The full stack — gates, Postgres ledger, Langfuse, Redis cache — runs inside the customer's VPC. No prompt, output, or audit row leaves the perimeter. There is also a FedRAMP-compatible airgap mode.
Which AI coding clients does CTO Rail support?
Claude Code is live today. Cursor, Continue.dev, Aider, and Zed AI are on the roadmap and exposed via a JSON pre-/post-prompt hook contract, so any AI coding client that supports hooks can be integrated.
Which LLM providers does CTO Rail support?
OpenAI is live. Anthropic Claude (Bedrock and direct), Azure OpenAI, AWS Bedrock, and self-hosted Ollama / vLLM are on the roadmap. Per-gate provider routing is supported, so different gates can run on different LLMs.
How much does CTO Rail cost?
Pilots start in the low four-figures per month. Pricing scales with seats and gate volume. Two pilot slots are open for Q2 and Q3 2026. Email manjeet.singh@aiinfox.com or book a 30-minute demo.
What languages and codebases does CTO Rail work with?
CTO Rail is language-agnostic. The gates operate on prompts, outputs, file paths, and embeddings, not on language-specific ASTs, so the rail works the same way against Python, TypeScript, Go, Java, Rust, C#, and any other codebase your developers use.
What does the audit trail contain?
Every prompt, every output, every gate verdict, the actor, the project scope, the model used, the token count, and the dollar cost. Writes are idempotent with a deterministic dedup key, dual-written to Postgres and Langfuse, and exportable as a per-project audit pack for SOX, SOC 2, HIPAA, and board review.
What is the drift gate (G4) actually measuring?
G4 computes cosine similarity between the latest model output's embedding and the rolling 50-output baseline for the project. Below the soft threshold (default 0.30) it logs a warning; above the hard threshold it blocks the output before it lands in the developer's editor.
Who built CTO Rail?
CTO Rail is built by Aiinfox Pvt. Ltd., founded by Manjeet Singh — engineers who have shipped inside Fortune-500 enterprises and regulated fintechs. It is currently at v0.2.4 with active pilot deployments.