Secure AI Application Development :

Why Secure-by-Default AI Development Matters

Most AI applications are built first and secured later. The result is technical debt that compounds: control gaps surface during audit, audit findings force redesign, redesigns delay enterprise contracts. Securing AI after the fact is two to four times more expensive than building it secure from the first commit. LYFYE engagements start with the threat model, the audit log schema, and the compliance framework targets, then write code against those decisions. The deliverable is a working application that passes SOC 2, HIPAA, CMMC, or FedRAMP audit on first attempt rather than third.

What We Build

Production AI applications across four common shapes:

• User-facing AI chat applications with prompt injection defenses, output filtering, and tenant isolation
• Internal agentic systems with tool permission boundaries, approval gates, and audit telemetry
• RAG (retrieval augmented generation) platforms with vector store isolation and document provenance tracking
• AI-augmented dashboards and decision support systems with explainability and audit trails

The LYFYE Stack

Every engagement runs on the same proven foundation that powers LYFYE Studio, Facts, and lyfye.com.

• Frontend: Next.js 14 with App Router, React, TypeScript, Tailwind CSS
• ORM and database: Prisma with Neon serverless PostgreSQL
• Background jobs: Inngest for event-driven workflows and AI agent orchestration
• AI runtime: Anthropic Claude API for primary inference, Azure OpenAI for HIPAA-eligible deployments, fallback to self-hosted models for sovereignty requirements
• Authentication: Auth.js v5 with SAML, OIDC, and Microsoft Entra integration
• Audit telemetry: structured logs streamed to Azure Log Analytics, AWS CloudWatch, or your preferred SIEM
• Hosting: Vercel for production, with optional self-hosted Kubernetes for sovereignty requirements

Compliance-Ready by Default

Every deliverable is shipped audit-ready against your target framework. We do not retrofit compliance; we design to it from the start.

• SOC 2 Type II: 60+ Trust Services Criteria controls implemented and evidenced. Auditor-ready in months 5 to 6.
• HIPAA Security Rule: Technical safeguards (164.312) and administrative safeguards mapped and implemented. BAA-ready architecture.
• CMMC Level 2: 110 NIST 800-171 controls with AI-specific implementation. C3PAO assessment-ready.
• FedRAMP Moderate: NIST 800-53 rev 5 controls with AI RMF integration. 3PAO assessment-ready.
• ISO 27001: ISMS-aligned controls with Statement of Applicability authoring.

Engagement Model

Founder-led delivery with senior operators accountable for the work. No leverage pyramid, no offshore handoff, no rotating staff.

• Discovery and threat modeling (1 to 2 weeks, fixed fee): use case scoping, threat model authoring, compliance target selection, architecture sketch.
• Architecture design (2 to 3 weeks, fixed fee): full reference architecture, control mapping, telemetry schema, evidence collection plan.
• Sprint-based development (variable, 4 to 16 weeks): one-week sprints with deployable increments. Working software every Friday, not just status updates.
• Audit readiness (2 to 4 weeks, fixed fee): evidence pack assembly, mock audit, auditor handoff support.
• 30 days post-launch support: bug fixes, performance tuning, knowledge transfer.

Pricing Reality

Custom AI application development engagements typically run $150K to $750K depending on scope, compliance target, and integration complexity. Healthcare and federal engagements price higher because of the additional compliance overhead.

• Discovery and threat modeling: $25K to $50K (fixed fee, 2 weeks)
• Architecture design: $40K to $80K (fixed fee, 3 weeks)
• Sprint-based development: $200K to $600K depending on duration and scope
• Audit readiness: $30K to $60K (fixed fee, 4 weeks)
• Total typical engagement: $250K to $750K, 16 to 24 weeks

Who This Is For

Three buyer profiles where this engagement model fits cleanly. AI startups at Series A or B planning to enter regulated verticals (healthcare, financial services, defense, public sector) who need their first product to pass audit. Enterprise innovation teams building AI applications that will live alongside the company's compliance program and cannot afford to be the weak link. ISVs adding AI features to existing products who need the AI surface to inherit the existing compliance posture.

What This Is Not

We do not do generic web development. We do not staff offshore developers. We do not build no-code Bubble or Webflow applications. We do not take engagements where compliance and security are afterthoughts. If your need is a marketing site or a simple CRUD application without regulatory exposure, the right partner is a generalist agency at one-fifth the cost.

How to Engage

Two-step process. First, a 30-minute scoping conversation to confirm fit. We will tell you directly if your project is better served by another partner. Second, a paid discovery and threat modeling sprint that produces a fixed-scope engagement proposal with stated deliverables and timeline before any committed engineering work. Most clients move from first conversation to signed engagement in 2 to 3 weeks.