Infonaligy helps DFW teams of 10–300 turn AI from scattered experiments into governed, monitored operating systems. Strategy, custom agents, automation, DevOps, security, and training — delivered by an AI-native team, not a legacy IT shop adding AI as an afterthought.
Built across the platforms your team already trusts
Most organizations don't need another disconnected AI experiment. They need a managed operating model that says what's approved, where data can go, which workflows deserve investment, and who owns reliability after launch. That's what we build.
Teams adopt tools faster than leadership can set policy. We define approved use cases, data rules, and review paths before AI spreads.
Sensitive data leaks into public prompts and unmanaged plugins. We bring real discipline to access, identity, and data handling.
Experiments burn subscriptions and meetings with no operating case. We start with workflows, cost of delay, and measurable outcomes.
Promising pilots stall when they must connect to M365, CRM, or finance. We design around the systems and approvals you already run.
Many Dallas firms managed servers for two decades and discovered AI last year. We were built the other way around: an AI-first practice where agents, retrieval, evaluation, and model operations are the core discipline — backed by enterprise-grade security and governance.
Strategy → Build → Operate, owned end to end.
Focused AI services for leadership teams that need useful systems, controlled data, and an operating model that survives past the launch demo.
Prioritize the workflows, business case, guardrails, and adoption roadmap before you invest in tools.
Governed agents built around approved data, retrieval, human review, tool access, and audit trails.
Connect CRM, inbox, service, and finance so repetitive work moves with control — not chaos.
Version, test, monitor, and improve prompts, agents, retrieval, and model costs after launch.
Train teams on safe prompting, approved use cases, role-based workflows, and responsible AI habits.
Private AI environments, data-readiness audits, DLP guardrails, and compliance-aware rollout.
Mid-market teams don't need an open-ended AI experiment. We publish flat-fee starting points, scoped build ranges, and managed retainers so leadership can plan before committing.
Leadership briefings, AI readiness assessments, and shadow-AI risk reports that clarify where AI belongs.
Policy packages, pilot implementations, custom agents, connectors, and process redesign when a build is justified.
Ongoing optimization, office hours, prompt-library maintenance, quarterly reviews, and advisor support.
We treat AI as an operating layer, not a one-time rollout. Each step has an owner, control points, and a path into managed support.
Map workflows, shadow-AI usage, data readiness, risk, and the operating case before recommending tools.
Design the approved workflow, governance model, data boundaries, integrations, and human-review path.
Build or configure the system, train users, validate quality, and move only stable workflows to production.
Monitor usage, cost, reliability, model changes, and prompt drift, with executive outcome reviews after launch.
We never deploy AI that puts your sensitive data at risk. Every system we build uses private, secure environments — not public consumer accounts. Customer records, financials, and proprietary data stay under your control, always.
We don't ask you to rip and replace. Our integrations plug into your CRM, helpdesk, invoicing, and communication tools so AI saves time without changing how your team works.
CRM · Helpdesk · Finance · Comms — connected with control.
"Finally an AI partner that started with our workflows and risk, not a tool demo."
"They treated data governance as the starting point, which is exactly what our board wanted to see."
"The managed retainer means our automations actually keep working after launch."
Illustrative commentary shown while client case studies are finalized.
AI adoption doesn't need to start as a large fixed project. We can consult hourly, but most clients prefer a prepaid retainer block they use at their discretion — no minimum monthly usage and no expiration. Every hour is documented clearly. Flat project pricing applies only when scope is defined, such as building an agent, automation, or secure integration.
We're AI-native. Our core discipline is agents, retrieval, evaluation, and model operations — backed by enterprise security and governance. Rather than a legacy IT shop adding AI to an existing service menu, we were built to deliver governed AI systems and the operating model around them.
If your team spends time on repetitive work — data entry, report generation, customer follow-ups, answering the same questions, scheduling — AI can help. We offer an initial assessment that identifies the tasks costing you the most time and shows exactly what can be automated safely.
We're vendor-neutral and work with ChatGPT, Claude, Gemini, Microsoft Copilot, Azure OpenAI, Google Vertex AI, Zapier, Make.com, Power Automate, HubSpot AI, and custom-built solutions. We start with practical tools your team can adopt safely, then recommend automation or custom agents only when they fit the workflow and budget.
The short answer: don't paste sensitive data into public ChatGPT. We deploy private AI instances, set up data-loss-prevention policies, train your staff, and align to HIPAA, SOX, or whatever regulations apply to your industry.
Yes. Our home market is DFW and most clients are local, but our consulting, automation, and agent work can be delivered remotely across Texas and the US.
We don't just advise — we take products from idea to production. Two platforms we defined, built, and deployed end to end:
Subscription lawn care with AI agents for customer support, lead generation, and marketing content.
An AI marketing platform with agents for content generation, editing, competitor monitoring, and support.
Rooted in Dallas–Fort Worth, we serve five metros plus remote delivery nationwide — every market our competitors cover, and more.
Across DFW: Dallas, Fort Worth, Plano, Frisco, Richardson, McKinney, Allen, Irving, Arlington, Garland, Carrollton, and Addison.
Identify the workflows, risks, data boundaries, and operating model before AI spend turns into another unmanaged tool rollout.
Infonaligy