Why We Built TextSynth: Intent to Action, Reliably

The challenge: smart agents that can't do their jobs

We've spent years building marketing automation and AI workflows for companies across industries. The pattern is always the same: the AI understands what you want, but it can't reliably do it.

Ask an agent to "schedule a meeting with Sarah next Tuesday at 2pm" and it might create the event on the wrong calendar. Or pick the wrong Sarah. Or miss the timezone. The model understood you perfectly. The execution failed anyway.

This is the semantic-functional gap - the space between what you mean and what the system does. And it's the reason most AI agent projects stall after the demo.

The models are smart enough. The tools exist. The APIs are documented. But the translation layer - the part that turns natural language into reliable action - is broken. Current solutions fail 15-40% of the time on real-world tool calls. That's not a rounding error. That's unusable.

"We kept building agents that worked in demos and fell apart in production. The problem wasn't the AI. It was the plumbing between the AI and the tools."

- Internal development notes

What we're building: intelligent agent routing that actually works

TextSynth is an SMS-first AI platform that routes your requests to specialized agents built to execute reliably.

Instead of one general-purpose AI trying to do everything, TextSynth maintains a network of purpose-built agents - each one optimized for a specific type of task. A scheduling agent. A CRM agent. A research agent. A writing agent. You text what you need, and the system routes to the right agent with the right context.

The core innovation is the Resolution Layer - a patent-pending system that handles the ambiguity problem before it causes failures. When a request is unclear or could map to multiple actions, the system doesn't guess. It asks targeted clarifying questions, quantifies its own uncertainty, and only executes when confidence is high.

This isn't a chatbot. It's infrastructure. The goal is to collapse the app stack into a conversation - letting you manage work from anywhere by texting agents that actually do things.

Why SMS? Why not another app?

Because you already have too many apps.

Every productivity tool promises to save time, then demands you learn a new interface, check another dashboard, and manage another notification stream. The app stack keeps growing. The work doesn't get easier.

SMS is universal. It works on every phone, requires no download, and fits into how you already communicate. Research shows mobile workers are more productive when they can operate from their primary device without context-switching between apps.

TextSynth is mobile-first, not mobile-friendly. The entire experience is designed around the constraint of a text conversation - which forces clarity, simplicity, and reliability.

The architecture: multi-agent routing with built-in uncertainty handling

Most AI agent frameworks treat tool-calling as a solved problem. It isn't.

When an LLM tries to translate a natural language request into an API call, it faces what researchers call the "intent-to-invocation fidelity" problem. The model has to select the right tool, extract the right parameters, format nested JSON structures correctly, and handle implicit requirements - all in one shot. Studies show accuracy drops 40+ percentage points when tool catalogs grow beyond 50 options.

TextSynth approaches this differently:

Specialized agents - Each agent handles a narrow domain with a small, well-defined tool set. A scheduling agent only deals with calendar operations. Fewer tools means higher accuracy.

Intelligent routing - A routing layer analyzes incoming requests and matches them to the right agent based on intent, context, and required capabilities. The router doesn't execute - it delegates.

Resolution Layer (SAKE Stack) - When requests are ambiguous, the system engages a structured clarification flow. It identifies what's missing, asks specific questions, and waits for confirmation before executing. No guessing.

Fallback handling - Every integration has a graceful failure mode. If an agent can't complete a task reliably, it says so - and offers alternatives instead of failing silently.

What this enables

Work from anywhere. Text "reschedule my 3pm to tomorrow" and it happens - without opening a calendar app, checking which calendar, or wondering if it worked.

Connect your tools. Bring your own integrations. TextSynth is designed to work with the systems you already use, not replace them.

Trust the execution. When the system says it did something, it did it. When it's uncertain, it asks. No more checking behind the AI to make sure it didn't hallucinate an action.

Scale without switching. As your needs grow, add agents. The interface stays the same: text what you need, get it done.

Where we are now

TextSynth is in active development with early access planned for Q2 2026.

We've filed a provisional patent on the Resolution Layer architecture. The core routing system is built. We're now onboarding design partners to validate use cases and refine the agent library before public launch.

If you're an early adopter who wants to work from your phone without trusting broken AI tools, we want to talk.