Products

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Products by Hatchery

Product layers your company can build on.

Mentis, Aegis, Axis, and Connect give serious product work reusable foundations: application structure, protected AI, interface quality, and customer activation.

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MentisJava product backbone

AegisAI Security & Governance

AxisExperience system

ConnectActivation layer

Product family Mentis, Aegis, Axis, Connect, operations

Product environment

Code, product layers, AI protection, and operations working as one.

For your company, the value is one controlled software environment: Java services, Mentis, Aegis, Axis, Connect, data, security, and DevSecOps moving together from build to launch.

Java code Services, APIs, business logic

Data model SQL, workflows, reporting

DevSecOps AWS, monitoring, recovery

Mentis Java product backbone Aegis Protected AI path Axis Interface system Connect Customer activation

Hatchery-built Your product Designed, coded, connected, protected, launched, and operated.

Custom SaaS Product workflows users can trust

Protected AI Approved models, logs, guardrails

Production operations Security, monitoring, support

A product environment for the path ahead.

Your company gets practical layers for building, protecting, and improving serious software.

Mentis gives your product a proven Java foundation for shared services, utilities, and security patterns.

Routing, sessions, database pooling, users, roles, permissions, and long-term service structure
Utility layer for math, calendars, data processing, SMS, email, and product workflows
Security services for authentication, authorization, protected data access, audit paths, and AI/RAG boundaries

Aegis helps your organization use AI safely by governing models, prompts, tools, identities, data, and responses.

IAM-aware access, approved model routing, policy checks, and guardrails
Token usage, spend, tool calls, traces, and user activity in one control path
Bedrock, AgentCore, MCP, PrivateLink, KMS, and CloudTrail-aligned patterns

Axis gives complex products a polished interface system: app shell, navigation, layout, theme, mobile behavior, and reusable patterns.

Consistent UI for complex operational tools
Dark mode, mobile-first behavior, app-style navigation, and Progressive Web App (PWA) support
Design patterns that help your product evolve cleanly

Connect turns customer touchpoints into branded, measurable paths across QR codes, links, profiles, APIs, and campaigns.

Custom branded QR codes and intelligent link shortening
Digital profiles and customer-facing destination pages
API-connected campaigns, integrations, and attribution paths

Try Hatchery Connect View case study

Aegis + DevSecOps

Keep trade secrets and company data out of public AI tools.

The risk is not one model brand. The risk is unmanaged use: customer data, source code, contracts, product plans, and trade secrets moving through accounts your company cannot see.

Aegis puts AI access behind governed routing, identity, approved tools, policy checks, logging, AWS-native patterns, and fallback planning.

Aegis is priced as a managed service with a percentage surcharge over your monthly AI/model spend. As usage volume increases, that percentage drops.

Talk to Hatchery about protected AI

ProtectKeep proprietary data, prompts, files, and source code in controlled AI paths.

GovernDefine approved users, models, data, tools, and review rules.

RouteUse Bedrock, approved model paths, Gateway boundaries, and customer tools.

ActConstrain agents with identity, memory policy, approvals, and rollback paths.

ObserveTrack model calls, tool calls, tokens, spend, traces, and users.

EvolveAdd models, connectors, evaluations, policies, and dashboards over time.

Risk evidence

Direct AI use creates blind spots.

The point is not to block useful AI. The point is approved access, visible usage, data boundaries, model routing, monitoring, and fallback plans.

78% of AI users bring their own AI tools to work. 39.7% of AI interactions involve sensitive data. 1 in 5 organizations reported a breach tied to shadow AI. 158 source-code sharing incidents per 10,000 users per month were observed for ChatGPT. Model volatility Claude status history shows repeated elevated-error incidents across models. OWASP tracks prompt injection, data exposure, denial of service, and excessive agency. 700M weekly ChatGPT users were cited by OpenAI; scale makes unmanaged use a governance issue. 4,500 shared ChatGPT conversations appeared in Google results during a public-link indexing incident. 370K+ Grok chats were reported indexed after shared links became public. Grok xAI says Grok interactions may be used for training, with controls and limited review. 3.56B people used a Meta family app daily in March 2026, expanding the consumer AI surface. Meta AI Meta says AI chat information may be retained, personalized, and shared with trusted partners.

Production discipline

Built to launch and keep moving.

Product layers only matter when they are backed by secure architecture, monitoring, backups, recovery, testing, and ownership.

Built for production

Architecture, data models, APIs, UX, CI/CD, and release discipline stay connected.

Operated with evidence

Monitoring, logs, performance data, backups, and recovery practices make systems easier to trust.

Protected by default

Access control, encryption, audit trails, and compliance support are part of the product plan.

Ready to evolve

New workflows, model changes, integrations, reporting, and customer requirements can be absorbed over time.

Hatchery product family

Four product layers. One delivery model.

Your company gets the structure serious software needs: a foundation for the application, a clear experience system, connected customer touchpoints, and a protected path for AI and operations.