Finance closes the books at 11pm. Support drowns in tickets that arrive un-triaged. Procurement chases the same questionnaires for the tenth time. IT wakes at 2am to work out what changed. InTouch AI takes that recurring work off your people — reliably, on schedule, and under the controls your auditors require.
AI sits at the center of this platform — the vault, access control, scheduling, and audit trail sit behind it. The incumbents bolt AI onto an older core. You can't bolt on a center.
InTouch AI automates the work that actually runs an enterprise — Finance, Customer Service, Sales Support, IT & Infrastructure, Internal Audit. You describe the outcome in plain language and InTouch AI builds, runs, and maintains the automation — with the governance, access control, and audit trail an enterprise needs.
Pick the corner of the org you own. The pattern is always the same: a Friday-night fire drill becomes a Monday-morning briefing.
Before: a multi-day close across spreadsheets, ERP, and OLAP cubes; an analyst hand-writes the variance commentary at 11pm.
After: extract → transform → load → calculate → a written variance narrative → report distributed — while the office is empty. Senior analysts spend Monday answering questions, not building the deck.
Before: tickets pile up. Categorization is wrong half the time. SLAs slip. Senior agents rewrite the same five replies.
After: every ticket arrives classified, prioritized, routed, and with a draft reply ready to edit-and-send. Severity-1s page on-call automatically. The agent's day starts at “review,” not “triage.”
Before: RFQs land in a shared inbox. Quotes go silent and nobody follows up. The pipeline lives in someone's head.
After: incoming RFQs triaged by scope and urgency, quotes chased on a 7/14/21-day cadence, win/loss logged. The reps sell; the system does the nagging.
Before: an alert fires at 2am. On-call spends 20 minutes finding what changed, who's affected, and whether it's happened before.
After: the alert is enriched on the way to the pager — recent deploys, related tickets, similar past incidents, current customer impact — delivered as a structured incident summary on the responder's channel. And when a workflow itself stumbles, the platform reads the failure: it knows why, smart-retries, refreshes the expired token, and surfaces the one sentence that matters. “It broke. Here's why. I fixed it.” Mean time to context drops to seconds.
Before: every cycle, someone manually pulls evidence from a dozen systems and assembles it into a binder by hand.
After: evidence collection runs on a schedule, every action is already logged with user and timestamp, and the control package assembles itself. The audit trail isn't a project — it's a by-product of how the platform runs.
Before: weeks of back-and-forth. Procurement chases questionnaires, security chases SOC reports, legal chases NDAs.
After: vendor data pulled from N sources, synthesized into a one-page risk packet across financial / security / regulatory dimensions, and a same-day decision package handed to the committee. Vendors go live in days, not weeks.
That's six. There are more — HR onboarding, resume screening, the Monday report every exec quietly dreads.
See the full set, by department →The higher the stakes, the more you dial toward certainty. The enterprise lives on the right of this scale — and InTouch AI is the platform that gives you the whole dial.
Let it decide.
Describe the task in your own language; the AI assistant reasons it out and acts — every run. Maximum flexibility, zero setup. Best when work changes shape constantly and the stakes are low.
You decide where AI belongs.
Your team designs the automation and places AI tools at the points that need judgment — classify, extract, draft, summarize — with deterministic tools doing the rest. You're in the loop as the architect: you choose exactly where AI operates and where it doesn't.
Locked, repeatable, audited.
Once a workflow is proven, run it with no AI in the running path — identical every time, zero AI cost per run, full audit trail. Best for production, compliance, and scale, when “the same way, every time” is the requirement.
You don't choose once for the whole company — you choose per use case. Prototype something in pure AI, then graduate it to a zero-AI-cost, identical-every-time, fully-audited workflow as it earns trust. That's the determinism dial — and nobody else gives it to you. No pure-AI agent and no legacy scheduler can offer it.
Good. That's the question your security, audit, and procurement teams will ask. Here's the part the AI-bolted-on startups can't answer: this governance is production-hardened in the Fortune 500 — AI is the new center, and the trust floor underneath it is enterprise-grade. Here's the short answer; the full architecture and security model are one click further.
Granular permissions by role, area, and object. Control who can see, edit, or run each workflow. LDAP / Active Directory integration; object-level security.
strongly encrypted vault — the trust floor. Workflows reference secrets by name — never pasted into scripts, config, or environment variables, and never exposed even to the AI itself. CyberArk integration for privileged access.
Every execution, every configuration change, every user action — timestamped and attributable. Your auditors get something to review; your team gets accountability built in.
Self-hosted and single-tenant. Your AI prompts and your data never leave your network — one server per organization, by design.
Immediate notification on any failure across eight channels (email, Slack, Teams, and more), with complete execution logs. No more “nobody noticed the workflow died three days ago.”
Everything the UI does, the REST API does — OpenAPI 3.0, ready for your portals, pipelines, and dashboards. Integrates with the systems you already run; it doesn't replace them.
Roles and encryption are table stakes. What an enterprise operation truly values is control over how AI gets used — which models, at what cost, under what policy — and the reach to run it from anywhere. That's the layer we've built.
Grant exactly what each user and group can touch — which AI providers, tools, monitors, skills, workflows, and credentials. Deny-by-default, enforced at execution. Real governance, not roles on paper.
Every AI call metered — by provider, model, and project — with cost attribution.mdash; by provider, model, and project Every AI call metered — by provider, model, and project — with cost attribution.mdash; with cost attribution. Chargeback, budgets, and an audit trail for your AI spend. You can't govern what you can't measure.
Route every AI request through one governed gateway. Control which providers and models each team is allowed to use, centrally — a single policy point for all AI access.
Standardize the prompts your organization runs — versioned, reusable, and access-controlled. Oversight over how AI is used, instead of a free-for-all.
A native Android app and a Progressive Web App for iPhone and iPad. Monitor operations, review runs, and act on what needs attention — from anywhere, not just the office.
When a workflow needs attention, your phone knows. Push to Android and mobile web means nothing waits for someone to happen to check a dashboard.
This isn't a launch-day promise. The same engine has automated mission-critical operations at some of the largest enterprises on earth at enterprise scale — under their security, their credentials, their audit requirements.
Trusted in production by teams at
Fortune 500 customers across finance, manufacturing, technology, and retail
…and dozens more.
We'd rather you hear the boundaries from us than discover them in a POC.
We'll show you what it looks like automated on the AI-native platform — governed, audited, self-healing, and on your own infrastructure. The older way is done; this is what replaces it. Department, Team, and Enterprise licensing available.
Blue Isle · Miami, FL · 954-353-BLUE