We take your AI systems from fragile prototype to regulated production.

Stuck between a working AI demo and enterprise security approval? We step directly into your repository to fix auth vulnerabilities, enforce tenant isolation, and clear infosec audits in weeks.

Book an Architecture Review Take 3-Minute Readiness Assessment
⚡ 3-Day Architecture Turnaround 🛡️ Built for OSFI E-23, SOC 2, and PHIPA 💻 Direct Pull Requests in Your GitHub or GitLab Repo

Architecture Review

Fast outside evaluation to uncover code vulnerabilities, auth flaws, and scaling gaps before you launch.

3 to 5 Days Delivery →
Most Popular

MVP to Production

Hands-on engineering sprints in your repository to implement RLS, auth, rate limiting, and test suites.

2 to 4 Weeks Sprints →

Data & Governance

Open lakehouse data architectures, model risk management, and turnkey compliance evidence binders.

Custom Sprints →
Common Bottlenecks

Where Most AI Applications Break Before Launch

If your team is facing any of these four hurdles, we step directly into your codebase to fix the architecture and ship production PRs.

Bottleneck 01 Enterprise Sales Stalled

The Enterprise Security Questionnaire

Your sales pipeline is frozen because an enterprise customer's infosec team sent a 150-question vendor assessment asking for multi-tenant isolation proofs, encryption keys, and SOC 2 controls.

How TensorVault Solves It

We implement Row-Level Security (RLS), role-based access control, encryption in transit/rest, and generate the technical evidence required by enterprise security officers.

Bottleneck 02 Prototype Fragility

The Prototype Multi-Tenancy Crash

Your prototype worked great in local testing with a single user, but concurrency, unindexed database queries, and lack of schema validation cause crashes under real production traffic.

How TensorVault Solves It

We refactor monolithic bottlenecks, implement connection pooling, optimize indexing, and introduce strict input validation to handle high concurrent load safely.

Bottleneck 03 Model Safety & Cost

Unbounded LLM Calls & Data Leakage

LLM inference costs are spiraling, prompt injection vulnerabilities expose system instructions, and customer PII is being sent directly to external model APIs without scrubbing.

How TensorVault Solves It

We engineer prompt firewalls, automated PII sanitization pipelines, semantic caching to cut API spend by 40%+, and cryptographically hashed prompt-response audit logs.

Bottleneck 04 Regulatory Uncertainty

Upcoming Regulatory & Compliance Audits

Regulators (OSFI E-23 in banking, PHIPA/HIPAA in health, Quebec Law 25) require documented model lineage, bias testing, and explainability records before you can go live.

How TensorVault Solves It

We build model risk management systems, drift monitors, and turnkey compliance binders that satisfy regulatory auditors on the very first review.

How We Work With You

Three Clear Engagement Paths

Whether you need a rapid outside technical evaluation or full in-repo engineering sprints, we deliver concrete code and documentation.

Entry Point 3 to 5 Days Delivery

Rapid Architecture Review

Fixed-Scope Outside Audit

An independent, senior engineering assessment of your existing codebase and planned architecture. We uncover security vulnerabilities, concurrency limits, and compliance blockers before you commit valuable engineering cycles.

✓ Full codebase, API, and cloud infrastructure evaluation
✓ Authentication, authorization, and tenant isolation check
✓ LLM prompt defense and data leakage vulnerability scan
✓ Regulatory readiness check (OSFI E-23, PHIPA, SOC 2)

What You Receive

📄 25-Point Scorecard PDF 🗺️ Threat Matrix ⚡ Prioritized PR Backlog
Start with an Architecture Review →
Flagship Engineering Sprint

MVP to Production

Hands-On In-Repo Hardening | 2 to 4 Weeks

We step directly into your GitHub or GitLab repository with senior engineers to harden your prototype into an enterprise-ready system that passes security reviews and scales under load.

A Readiness & Threat Audit

Deep-dive into existing code, database schemas, and external API integrations.

  • ✓ Auth & role hierarchy review
  • ✓ Input validation & injection risks
  • ✓ Concurrency & database query audit
B In-Repo Hardening Sprints

Direct implementation of fixes delivered via peer-reviewed pull requests.

  • ✓ Enterprise auth & RLS implementation
  • ✓ Rate limiting, schemas, sanitization
  • ✓ Automated test suites & telemetry

What You Receive

💻 Merged Pull Requests 🛡️ RLS & Auth Matrix 🧪 CI/CD Test Suite 📑 Infosec Evidence Package
Discuss Your Build →
Downstream & Specialized

Data Lakehouse & Model Governance Engineering

Once your MVP is hardened, your data layer needs to scale and meet formal regulatory requirements. We build vendor-neutral open table format lakehouses (Apache Iceberg, Delta Lake) and generate the technical evidence binders needed for OSFI E-23, PHIPA, and SOC 2 audits.

📊 Apache Iceberg Pipelines 🛡️ OSFI E-23 Model Lineage 🔍 Adversarial Red-Teaming
Request Data & Governance Scope → Or take free 3-minute readiness assessment →
Interactive Build Navigator

Where is your team right now?

Select your current situation to see the exact sprint scope, deliverables, and how your architecture transforms from fragile prototype to production.

In-Repo Engineering

We Write Production Code, Not Slide Decks

We don't hand you an 80-page PDF checklist and walk away. We open peer-reviewed pull requests directly in your GitHub or GitLab repository.

github.com/your-org/ai-core-service / pull/42
✓ CI/CD Tests Passing
feat/enterprise-rls-and-prompt-defense Created by TensorVault Engineering Team

Hardened Multi-Tenant Isolation, Semantic Cache, and PII Sanitization

Implemented PostgreSQL Row-Level Security (RLS) policies per tenant, integrated streaming PII regex masking before LLM inference, and added automated integration test suite for SOC 2 compliance.

// 1. Database Tenant Isolation Policy (PostgreSQL)
+ ALTER TABLE tenant_ai_documents ENABLE ROW LEVEL SECURITY;
+ CREATE POLICY tenant_isolation_policy ON tenant_ai_documents
+ USING (tenant_id = current_setting('app.current_tenant_id')::uuid);
---
// 2. Prompt Injection Defense & PII Redaction Pipeline
- const response = await openai.chat.completions.create({ model, messages: rawUserPrompt });
+ const sanitizedPrompt = await tensorVaultGuard.sanitizeInput(rawUserPrompt, { maskPII: true });
+ const cached = await semanticCache.get(sanitizedPrompt.hash);
+ if (cached) return cached;
+ const response = await securedInferenceClient.execute({ prompt: sanitizedPrompt });
+ await auditLogger.recordInference({ tenantId, promptHash: sanitizedPrompt.hash, tokens: response.usage });
✓ Zero architectural debt left behind
✓ Documented with Architecture Decision Records (ADRs)
✓ Clean handoff to your internal team
How We Work

Four-Week Engineering Execution

Fast, focused, and predictable. We operate directly in your codebase to eliminate technical debt and clear compliance hurdles.

01

Discovery & Threat Model

Repository onboarding under NDA, architecture breakdown, data flow mapping, and threat modeling across your stack.

Days 1 to 3
02

Readiness Audit

Identifying security gaps, broken auth patterns, unindexed queries, and regulatory compliance blockers.

Days 4 to 5
03

Hardening Sprint

Direct code implementation: RLS, input sanitization, rate limiting, automated tests, and structured logging.

Weeks 2 to 3
04

Verification & Handoff

Load testing, audit trail verification, compliance documentation sign-off, and seamless engineering handoff.

Week 4
The Difference

Why Engineering Teams Choose TensorVault

Traditional consultancies give advice. Generic dev agencies build fragile prototypes. We write production code engineered for regulated compliance.

Approach Big Advisory Consultancies Generic Dev Agencies TensorVault Engineering
Primary Deliverable 80-page slide decks and checklists Quick prototypes with hardcoded secrets Production Pull Requests in your repository
Execution Speed 3 to 6 month advisory marathons Unpredictable timelines 3-day reviews, 2 to 4 week sprints
Regulatory Fluency High-level theory, no code translation Zero compliance understanding Deep fluency in OSFI E-23, PHIPA, SOC 2
Code Ownership N/A (no code produced) Proprietary wrappers or vendor lock-in 100% your IP, documented and peer-reviewed

QueryBud Suite

AI-powered analytics demonstration. Secure, governed, and compliant by design.

Enterprise AI Analytics Platform

Tools for intelligent document retrieval, data extraction, and natural language analytics, built with governance and security as core principles.

Role-based access & audit logging (SOC 2 ready)
PII detection & data masking (Privacy by design)
Full query audit trails for explainability
Analytics Dashboard
AUDIT READY SECURE
FAQ

Frequently Asked Questions

Everything you need to know about our sprints, code access, and deliverables.

How do you access our codebase and protect our intellectual property?

We execute mutual non-disclosure agreements (NDAs) before touching any technical asset. Repository access is granted via scoped GitHub or GitLab collaborator permissions. All code modifications are delivered as peer-reviewed pull requests. We strictly never use, store, or train AI models on your proprietary source code or customer data.

What is the exact deliverable from an Architecture Review?

You receive a comprehensive 25-point Executive Scorecard PDF, a technical Threat Matrix detailing all security, authentication, and scaling vulnerabilities, and a prioritized remediation backlog with clear code fix instructions, delivered in 3 to 5 business days.

How does the MVP to Production sprint work?

We start with a Production Readiness Audit of your codebase, identifying broken auth flows, unindexed queries, and scalability bottlenecks. We then execute a hands-on engineering sprint directly inside your repository, implementing authentication, role-based access controls, input sanitization, rate limiting, automated test coverage, and observability logging.

Can our internal engineering team work alongside you during the sprint?

Yes. We operate directly within your existing development workflows (GitHub, GitLab, Linear, Jira). We pair with your team, document architectural decisions in code comments and ADRs, and conduct seamless handoffs so your engineers can scale the codebase with confidence.

What compliance frameworks do you support?

We specialize in Canadian and US regulatory standards: OSFI E-23, PHIPA, PIPEDA, Quebec Law 25, SOC 2 Type II AI controls, NIST AI RMF, and Health Canada SaMD guidance.

Supported By

Accelerating our growth with the Venn Innovation Garage Program, helping tech companies scale securely.

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Ready to Ship Production-Grade AI?

Let us review your architecture or harden your prototype for enterprise review. Get started with a fast, fixed-scope 3-day engagement.

Book an Architecture Review Run Free 3-Minute Assessment