01
Brief
Start with the morning question: what do I need to do today? We define the workflow, the daily output, the source systems, the success metric, and the human review point.
Shoal AI
Know what needs to happen today. AI for real workflows.
Shoal AI builds automation systems that connect workflows and tasks with AI agents. We integrate email, CRM, docs, research, calls, internal systems, internet context, and external data sources so SMBs and enterprises can focus on what matters most.
Daily priority queue
Internal and external data
Agents with review loops
Shoal AI
Approach
A specialist partner for connecting workflows, data, and AI agents.
Most teams do not need another chatbot. They need a system that pulls the right context from internal tools, internet sources, and external data feeds, then says what needs attention now: the reply, the deal, the research thread, the blocked task, the stale account, the next message, or the decision waiting on a human.
Shoal maps the operating context, connects the systems, codifies the workflow, and turns repetitive knowledge work into automation systems that can be inspected, corrected, and improved.
Process
How it works.
02
Structure
We connect internal systems, external data, and internet sources through APIs and MCP, then shape the data into entities, relationships, states, policies, confidence levels, and actions that agents can use reliably.
03
Workflow
We ship the first command center: a priority queue, inbox-to-do workflow, revenue operations view, research brief, internal memory surface, or agent-assisted operating doc.
04
Refine
The first version runs with real work. We tune prompts, data shape, permissions, review rules, and output format around the team's judgment and daily rhythm.
Why Shoal AI
What to expect.
Three commitments on every engagement.
01
Daily clarity comes before automation.
The first job is reducing cognitive load: collect the context, sort the work, show the why, and make the next action obvious before anything runs automatically.
02
Your existing tools stay the source of truth.
We build around the systems you already use: CRM, Gmail, Notion, Slack, docs, spreadsheets, databases, BI tools, and custom APIs. AI becomes the operating layer that reads from and routes work back to the canonical systems.
03
Every workflow is custom to the work.
Each command center reflects the workflow it serves: triage, follow-up, research, account management, project execution, internal support, or executive operating context.
Systems
Automation systems for workflows where context, reliability, and speed matter.
Inbox
Inbox to action.
Turn emails into prioritized to-dos, waiting-for lists, agenda items, follow-up drafts, project updates, and review-ready daily operating docs.
Revenue Ops
Who needs attention today?
See stale deals, high-priority accounts, relationship history, follow-up timing, next messages, handoff notes, and CRM cleanup work in one queue.
Research Ops
Research context without the reload.
Track internet sources, external datasets, entities, companies, calls, transcripts, documents, market context, and open questions into briefs that preserve source links.
Business Ops
A priority layer across the business.
Bring customers, projects, owners, decisions, blockers, revenue context, and internal tasks into a daily view of what needs movement.
Knowledge Bases
Internal and external memory.
Build structured knowledge bases from docs, calls, threads, databases, internet sources, external feeds, and decisions so agents can answer with context instead of generic recall.
Agents + MCP
Execution with controls.
Use MCP, structured data, external data connections, and agent workflows to summarize, draft, route, update, and escalate with source requirements, permissions, and review gates.
A small specialist team for workflow-specific AI systems.
Focus
AI automation systems, daily command centers, inbox triage, revenue operations, research operations, business context, internal memory, and external data workflows.
Model
Scoped integrations, fast first versions, workflow-specific agents, and refinement against live work, with clear review rules before automation.
Stack
Structured data, MCP, agents, knowledge bases, internet access, external data feeds, Claude, Codex, CRM, Gmail, Notion, BI tools, internal databases, cloud workflows, and custom APIs.
FAQ
Common scoping questions.
01
Where do we start?
Pick one workflow with clear pain: inbox triage, revenue follow-up, research prep, executive priority context, internal support, or a daily operating answer.
02
How do you keep outputs reliable?
We separate deterministic data assembly from AI reasoning, include source links, expose confidence and missing data, and keep review gates around decisions or actions that need judgment.
03
What do we need for a first scope?
A sample daily output, access constraints, the source systems involved, current manual steps, success metric, review owner, and the first workflow you want running.
Bring one workflow. We will turn it into a daily command center.
Start with the highest-friction process: inbox triage, revenue follow-up, support routing, research prep, executive context, team training, or an internal workflow that needs structured context.