STRATEGIC AI EXECUTION FOR MODERN TEAMS

Stop Losing Revenue to Manual Handoffs and Fragmented Systems

Deploy AI agents that own your workflows end‑to‑end—coordinating across tools, teams, and edge cases instead of relying on people to push every task along.

Dyntyx designs and runs orchestrated AI agents that move work forward, escalate the exceptions, and give you full visibility into every step, so cycles shrink and dropped balls disappear.

While most “AI bots” automate a single step and stall, Dyntyx agents carry full workflows across email, CRM, support, and finance so you see real throughput gains in weeks—not quarters.

60%
Hands-Free Workflows

Fewer manual touches per workflow

40%
Quicker Turnaround

Faster delivery from request to done

70%
Less Status Chasing

Reduction in status‑chasing and follow‑ups

8-12
wks
Time to Launch

To launch your first orchestrated agent

HOW WE WORK

What you get

Assistants that live in your tools
- We plug into email, chat, CRM, project tools, and other systems you already use.
- Your team doesn’t need a new app—work just starts happening for them.

Multi‑step workflows, not one‑off bots
- Our assistants can handle many steps in a row, not just a single action.
- They keep context, move work between systems, and know when to involve people.

Smart escalation
- You set clear rules for when the AI should ask a human to review or decide.
- Routine tasks stay automated; tricky, sensitive, or high‑risk cases go to your team.

Full visibility
- Every action is logged so you can see what happened and change the rules when needed.
- You always know which assistant did what, and why.

Weeks 1–2: Pick and map a workflow

We choose one important process, map the steps, and define what ‘good’ looks like.

1

Weeks 3–4: Design your assistants

We design how the assistants will work, what tools they touch, and when humans get involved.

2

Weeks 5–8: Build and test in the real world

We connect to your tools, run on real data, and refine based on your team’s feedback.

3

Weeks 9–12: Launch and expand

We go live, monitor results, and extend the same approach to more workflows.

4

Use Cases / Real Workflows

Launch your first orchestrated assistant in 8–12 weeks and see hours saved, faster cycles, and fewer dropped tasks from week one.

Customer intake & routing

New request comes in. The assistant reads and classifies it, checks your CRM for history, and sends it to the right person based on urgency and type. Your team gets the full context in one place and follow‑up happens automatically.

Financial process automation

An invoice arrives. The assistant pulls out the key fields, checks for duplicates or fraud signals, routes for approval when needed, processes payment, and updates your accounting system. Your team reviews edge cases instead of keying data.

Contract review & automation

New contracts come in. The assistant extracts key terms, checks for policy issues, flags unusual clauses, and routes anything risky to legal. Once approved, it archives the contract and notifies the right stakeholders.

Sales operations

A deal moves forward. The assistant updates the CRM, checks stock or capacity, alerts the right teams, sends a clean update to the customer, and tracks milestones. Reps spend more time selling and less time updating systems.

Mission

Most automation only handles the easy, straight‑line version of a process. Real work is messy—exceptions, handoffs, and constant context‑switching. Our mission is to build AI assistants that can handle that real‑world complexity so your business keeps moving without your team pushing every step along.

Vision

We believe the future isn’t ‘AI tools your team occasionally uses,’ but trusted AI teammates that own whole chunks of execution. When assistants can coordinate across email, CRM, project tools, and finance systems—and know when to involve a human—whole categories of busywork disappear. We’re building toward that future, one workflow at a time.

Mission Image
faq’s

Frequently Asked Questions

1
What if we don't have technical expertise?
2
What's the difference between hiring consultants and building in-house?
3
How do we know if AI is right for our business?
4
Can you work with our existing tools?
5
How long does it take to deploy a working agent?
6
How do you measure success?