Starting with consulting firms and agencies

Turn company knowledge into executable workflows

Connect SOPs, client calls, docs, and project history. We map how your team works and convert it into AI workflows that prepare deliverables, follow-ups, research, and execution plans with human approval.

Problem

Your best processes are trapped in messy knowledge

Service firms run on repeated client delivery, but execution quality still depends on fragmented context and senior memory.

SOPs are static and rarely followed

Process docs exist, but they are disconnected from actual execution and quickly drift from real work.

Client context is buried in calls, chats, and docs

Critical requirements live across transcripts, Slack, WhatsApp, and notes, making handoffs slow and risky.

Deliverables depend too much on senior people

Junior teams struggle to reproduce quality because the operating playbook is in people’s heads, not systems.

Generic AI tools don’t understand your workflow

They can draft text, but they miss your firm’s process logic, output standards, and project history.

How It Works

From SOPs and client calls to AI-run operations

Connect your existing company knowledge, map repeatable work patterns, and run workflows with control points built in.

1

Connect your knowledge

Upload SOPs, meeting transcripts, docs, past deliverables, and client context.

2

Extract workflows

We identify repeatable processes, decision points, required inputs, approval steps, and output formats.

3

Run with approval

Your team launches AI-assisted workflows for reports, follow-ups, research, task plans, and client deliverables with humans reviewing critical steps.

Use Cases

Built for repeatable client work

Start with one high-frequency workflow, prove speed and consistency gains, then expand across teams.

Client call ->

Summary, risks, next steps, and follow-up email.

SOP ->

Automated checklist and execution workflow.

Past reports ->

New client-ready draft in your firm’s format.

Research docs ->

Synthesized brief with sources and action items.

Onboarding docs ->

Implementation plan and task breakdown.

Internal chats ->

Project memory and decision log.

Differentiation

Not another chatbot. Not another wiki.

The wedge is operational execution: turning historical company context into workflows your team can repeatedly run.

Chatbots answer questions.
Context Layer generates workflows teams can execute.
Wikis store knowledge.
Context Layer operationalizes knowledge into steps, outputs, and approvals.
RAG tools retrieve documents.
Context Layer maps process logic and drives execution.
Generic agents lack business context.
Context Layer is built from your real operating history and delivery standards.
Product Preview

Connect source material. Generate a runnable workflow.

This preview shows the core product experience: input context on the left, executable workflow on the right.

Workflow Generator
Demo Mode
Input sources
SOP
Client onboarding process
Transcript
Discovery call
Past deliverable
Market research report
Internal note
Pricing assumptions
Generated workflow
1Extract client goals
2Identify missing data
3Draft research brief
4Generate follow-up email
5Create internal task list
6Request human approval
Human approval required before client-facing send.
Trust & Safety

Automation with control

AI handles repetitive execution. Your team controls the critical decisions.

Human approvals for critical actions
Source-backed outputs
Workflow versioning
Role-based access
Audit trail for every run

Make your company’s knowledge executable

Start with one workflow. Prove ROI. Expand across the firm.

Book a demo