--- title: "KeenDigit · Enterprise AI-native applications, built for production" description: "KeenDigit takes enterprise AI-native applications and workflows from use case to controlled production — grounded, evaluated, guard-railed, human-reviewed, and backed by the full stack beneath them." language: "en" url: "https://keendigit.com/en/" --- # KeenDigit · Enterprise AI-native applications, built for production KeenDigit takes enterprise AI-native applications and workflows from use case to controlled production — grounded, evaluated, guard-railed, human-reviewed, and backed by the full stack beneath them. ## Take AI-native ideas into *controlled production.* Enterprise AI-native application development We build AI-native applications and workflows around real enterprise systems — grounded in your data, evaluated before release, guard-railed, and human-reviewed. Every pipeline ships with its evidence attached. **Glass box**, not black box. ## Enterprise AI moves when the whole committee can *say yes.* One project · three decision lenses Business, technology, and risk leaders are approving the same system from different angles. We give each of them the evidence they need without splitting the project into three competing tracks. ## Turn a valuable workflow into an operating AI capability Business & innovation "We can see the opportunity. We need a credible path from use case to business operation." We frame the workflow, operating boundaries, and release path together so the project is tied to a real business decision — not a technology demo looking for a home. - A use case with a defined operating outcome - Clear human and system responsibilities - A phased path from pilot to production ## Ship AI features that hold up beyond the demo Product & technology "We tried an LLM demo. It impressed everyone, then fell over in production." We connect models to the data, APIs, applications, and infrastructure they depend on — then gate releases with evaluation, guardrails, observability, and rollback paths. - Features that pass eval gates before users see them - Continuous delivery, with instant rollback - Evidence on every release, not just a demo ## Keep control visible as AI enters the workflow Risk & governance "We need to know what the system can do, who approves changes, and when a person steps in." Our glass-box discipline keeps access boundaries, review checkpoints, release decisions, and change records visible from design through operation. - Documented approvals and access boundaries - Human-review rules for high-stakes decisions - A traceable record of what changed and why ## Reasons this holds up *in production.* Why KeenDigit Six delivery advantages that help business, technology, and risk leaders approve the same production system with confidence. ## Glass box, not black box Most AI is a black box. Every pipeline we ship carries its evidence — groundedness, eval scores, guardrail status, and the human-review trail — visible to you, always. **You see the controls**, not just the output. Eval · contract assistant **Groundedness:** 0.96 **Eval suite:** 48 / 50 **Guardrails:** PASS **Latency p95:** 840ms ## We work across the whole stack From the Linux server to the LLM. We can follow reliability, data, and access issues across the layers instead of treating the model as an isolated feature. - Server → LLM - One owner - No seams ## Independent by design Vendor-neutral assurance. We audit and verify your systems — including the third parties you already rely on. No conflicts, no lock-in. - Vendor-neutral - No lock-in ## Production-grade or it doesn't ship Grounded, evaluated, guard-railed, human-reviewed. Eval thresholds gate every release — nothing reaches users on hope. - Grounded - Evaluated - Guard-railed - Human-reviewed ## Continuous delivery, zero-regression Ship multiple times a week behind eval gates, with instant rollback. Improvement is constant; surprises aren't. - Eval-gated - Instant rollback - 3×/week ## You keep control Documented approvals, controlled access, structured handover. The docs, credentials, and code are yours to hold — by design. - Docs - Credentials - Code — yours ## AI is only as reliable as the stack *beneath it.* Product architecture AI-native applications sit at the top; data, APIs, existing software, infrastructure, and assurance make them production-ready. We work across those layers so reliability and evidence can flow up. Reliability & evidence flow up ## AI-Native Layer 01 · The product Intelligent apps and workflows, shipped to production with their evidence attached. ### AI-Native App Development LLM features to production — grounded, evaluated, guard-railed, human-reviewed. ### Workflow AI Integration LLMs embedded into existing workflows with audit trails and human-in-the-loop. ## AI-Ready Foundations Layer 02 · The substrate Clean data and reliable connectivity — what the models actually read from and write to. ### API Integration Secure auth and data mapping so your systems can talk to the model. ### Database Optimization Fast, reliable queries and backups — the data layer AI depends on. ### Web Refactoring Legacy PHP/JS modernized into a clean, AI-ready codebase. ## Run & Assure Layer 03 · The bedrock The infrastructure and independent assurance that keep everything above it dependable. ### Server Maintenance Patched, tuned Linux servers the whole stack runs on. ### Security Audit Independent audit of code, infra, and vendors. Verify, don't trust. ### Vulnerability Remediation, Security Updates & Hardening Fix known vulnerabilities, apply security updates, and strengthen the protection and resilience of your existing systems. - feeds · grounds · accelerates - secures · stabilizes · keeps trustworthy ## How clients move through it bottom-up — the path to production AI ### Frame the workflow Define the business outcome, operating boundary, data access, and human responsibility. All layers ### Prepare the foundations Connect the data and APIs, modernize what blocks delivery, and establish controlled access. Layer 02 ### Build & validate Build grounded, evaluated, guard-railed AI features with human-review checkpoints. Layer 01 ### Operate & Improve Continuous delivery, live evals, and monitoring keep it reliable as it grows. All layers ## An independent partner for *production-grade AI.* Company Our business history dates to 2002. Since 2026, our focus has been enterprise AI Native: independent, vendor-neutral delivery from business approval to production operation. KeenDigit reception Operating since 2002 · AI Native focus since 2026 **Location:** Sheridan, Wyoming United States **Delivery:** Global Remote-first **Language & billing:** English · USD **Engagement:** Independent Vendor-neutral What we believe Most AI is a black box. We build the kind you can put in production — **grounded, evaluated, guard-railed, human-reviewed** — and ship every pipeline with its evidence attached. Glass box, not black box. It's the same discipline we apply everywhere: documented approvals, controlled access, and traceable delivery. The goal is never to dazzle you with output — it's to show you the controls behind it. How we operate ## Documented approvals Nothing changes without a written, agreed scope. Every decision is on record. ## Controlled access Least-privilege by default. Access is granted, logged, and revoked deliberately. ## Traceable delivery Every change is attributable — what shipped, when, by whom, and why. ## Structured handover You keep the documentation, credentials, and control. No lock-in by design. ## Senior practitioners across the *enterprise AI stack.* The team An independent team organized around AI-native products, the foundations beneath them, and the controls that keep them accountable in production. ## AI-Native practice Layer 01 · Product Grounding, evaluation, guardrails, and human review for production AI. ## Foundations practice Layer 02 · Substrate APIs, databases, and legacy modernization — the AI-ready substrate. ## Run & Assure practice Layer 03 · Bedrock Infrastructure and independent security audit. Vendor-neutral. ## Michael Brennan Principal, AI Engineering AI-Native lead Production AI — grounding, evals, and the kind of systems that ship with their evidence attached. - LLM apps - Evals - Guardrails ## Kevin Zhao Lead Engineer, Platform Foundations lead APIs, data, and legacy modernization — the substrate that makes AI production-ready. - APIs - PostgreSQL - Symfony / Vue ## Simone Carter Security & Audit Lead Assurance lead Infrastructure, security audits, and independent vendor review. - Audit - Linux - Vendor review ## You meet who does the work No bait-and-switch. The senior who scopes it delivers it. ## Independent & vendor-neutral We audit third parties without conflict — including ones you already use. ## You keep control Documentation, credentials, and code stay yours. No lock-in by design. ## The evidence, *not just the pitch.* Selected work Representative engagements across AI-native delivery, the foundations beneath it, and independent assurance. ## Contract-review assistant Layer 01 · AI-Native A grounded LLM workflow with human review in the loop — shipped to production with its evidence attached. **Groundedness:** 0.96 ## Legacy platform, modernized Layer 02 · Foundations Legacy PHP/JS refactored into a clean, AI-ready codebase, with the data tidied behind it. ## Independent security audit Layer 03 · Run & Assure Inherited code, infrastructure, and vendors audited and stabilized before any new build began. Evidence is useful when it travels with the release — not when it is reconstructed after the decision has already been made. KeenDigit delivery principle ## AI Production Readiness Assessment ### Assess your path to *AI-ready production.* Not ready to scope the build? If the use case is clear but the systems beneath it are not, start with a scoped readiness assessment. We map the workflow, data, integrations, controls, and delivery risks before a build begins. Scoped AI readiness assessment · defined before access We review the target workflow, data sources, integrations, existing applications, infrastructure, and governance needs — then document what is ready, what blocks production, and what to do first. ### Scope in writing first. Nothing is touched until you've agreed exactly what we'll do. ### No access until you grant it. Least-privilege, logged, and revocable. ### You keep the assessment Use the findings to plan the next step with clear priorities. What the assessment covers ### Workflow & responsibility map Where AI acts, where people decide, and what the operating outcome requires. ### Data & integration readiness Sources, permissions, APIs, and gaps that affect grounding and delivery. ### Controls & review checkpoints Access boundaries, evaluation gates, guardrails, and human-review needs. ### A prioritized delivery path What to prepare first, what can be built next, and how rollout can be staged. ### Production foundation review Application and infrastructure constraints that could block reliable operation. ## The questions we *get first.* Before you ask What business, technology, and risk leaders ask before an enterprise AI project moves forward. ## Can you work with our internal team and existing vendors? Yes. We work as an **independent, vendor-neutral delivery partner**, with written responsibilities and interfaces between teams. The goal is one accountable production path, not another disconnected workstream. ## How do you handle enterprise data and access? Access is **granted by you, logged, and revocable**, on a least-privilege basis — and nothing is touched until the scope is documented and agreed. The documentation, credentials, and code stay yours throughout. Control is the default, not an upgrade. ## What does vendor-neutral mean for our architecture? No lock-in and no kickbacks. We don't resell anyone's platform, so our assessment isn't steering you toward a product we profit from. When we audit a vendor you use, our only incentive is to report what's true. ## Do we need to replace our existing systems first? Not necessarily. We identify which systems can support the target workflow, which connections or controls are missing, and what must change before production. The build can then be staged around the systems you already rely on. ## How do I know the AI you ship will actually hold up? Every pipeline ships **grounded, evaluated, guard-railed, and human-reviewed**, with eval thresholds gating each release and the evidence attached. Nothing reaches your users on hope — and you can see the controls, not just the output. ## What changed in 2026? KeenDigit has operated since **2002**. In 2026 we made enterprise AI Native the center of our delivery model, bringing the same full-stack engineering and structured handover discipline to grounded, evaluated, guard-railed, human-reviewed AI systems. ## Contact [Contact]() [Original page]() · [Content index]() KeenDigit LLC · Wyoming Filing ID: 2026-002106155 [Verify with the Wyoming Secretary of State]() © 2026 KeenDigit LLC · Sheridan, Wyoming, USA · All rights reserved.