SERVICES · ENTER AT ANY STAGE

Choose the stage you need. Each service has its own price.

Each service has a named deliverable and a fixed fee quoted before work begins. Start with one service or combine the stages into a 90-day Foundation.

Most clients start with one of two scopes.

Workflow Discovery

Over two to three weeks, we shadow your teams, map the workflows, and rank them by expected AI payback. The fixed-fee engagement gives you a ranked opportunity map and one architecture-and-cost sketch before you decide whether to fund a build. You keep both deliverables.
For you if: you want to see how we think before funding a build
FIXED FEE · QUOTED UPFRONT
BOOK A WORKING SESSION  >

The 90-Day AI Foundation

One accountable team runs assessment through deployment. The scope covers a governed knowledge system, controlled workflow execution, and your first supervised AI employee in a working channel. Go/no-go gates at weeks 2, 4, and 10 keep the engagement tied to one measurable workflow result.
For you if: you are ready to move one workflow into production
FIXED FEE · QUOTED UPFRONT
EXPLORE THE 90-DAY FOUNDATION  >

FIVE STAGES · ONE CLEAR DECISION AT A TIME

Inspect the stage, evidence, and decision before you choose a service.

Each stage names what it produces, who remains accountable, and what must be reviewed before the work advances.

01AssessWhere does AI pay?
01

Assess & plan

Before anything is built: find where AI can pay in your business and define the cost case.

AI readiness assessment

A structured review of your data, workflows, tooling, and governance, scored against five readiness stages.

For you if: you don't know where to start

DELIVERABLEREADINESS REPORT + STAGE SCORE

Workflow discovery

We shadow your teams, map the workflows, and rank them by expected payback, including the work we recommend leaving alone.

For you if: you suspect AI could help but can't name where

DELIVERABLERANKED OPPORTUNITY MAP · FIXED FEE · QUOTED UPFRONT

Cost & architecture sketch

For a chosen workflow: the operating design, data pipeline, and cloud-vs-local cost curve on one page.

For you if: you need a business case the board will read

DELIVERABLE1-PAGE ARCHITECTURE + COST CURVE

02StructureMake your data usable
02

Structure your knowledge

Your unstructured files become infrastructure: a vector database for meaning, a knowledge graph for facts.

Knowledge foundation build

Full ingestion of your files, shares, and mailboxes into a hybrid RAG stack: chunked, embedded, entity-extracted, cited.

For you if: answers exist somewhere but nobody can find them

DELIVERABLEVECTOR DB + KNOWLEDGE GRAPH

Freshness pipelines

Continuous sync to reduce stale knowledge: connectors, change detection, and staleness monitoring.

For you if: you built RAG once and it quietly rotted

DELIVERABLELIVE SYNC + STALENESS ALERTS

Context audit

We trace ten representative questions through your existing AI setup and show exactly where retrieval fails, and why.

For you if: you have AI but the answers disappoint

DELIVERABLERETRIEVAL GAP REPORT

03BuildBuild workflow controls
03

Build the workflow system

Skills, tools, memory, approvals, and audit trails that let a model carry a workflow reliably.

Custom workflow system

A system engineered for your workflow, with model choices, approvals, an audit trail, and escalation built in.

For you if: generic AI employee products do not fit how you work

DELIVERABLEPRODUCTION WORKFLOW SYSTEM

Skills authoring

Your procedures, written with your domain experts as versioned, testable skills, reusable across every AI employee.

For you if: your know-how lives in a few people's heads

DELIVERABLESKILL LIBRARY (VERSIONED)

Channel and system connections

Secure connectors into Microsoft Teams, Slack, and email, plus your CRM, ERP, and document systems as scoped tools.

For you if: AI should show up where work already happens

DELIVERABLECHANNEL + TOOL CONNECTORS

04DeployPut AI employees to work
04

Deploy AI employees

AI employees go to work inside your channels: supervised, cited, and measured against the workflow they own.

AI employee pilot

A supervised AI employee carries one workflow in one channel. Every consequential action requires human approval, and the log records what the AI employee flagged and the approver caught.

For you if: you want proof before commitment

DELIVERABLE6-WEEK SUPERVISED PILOT

  1. AI FLAGGED
  2. HUMAN CAUGHT
  3. LOGGED + APPROVED

Workforce rollout

Scale from one AI employee to a roster: shared skills, shared memory, per-team guardrails, and usage analytics.

For you if: the pilot worked and teams are asking for more

DELIVERABLEAI EMPLOYEE ROSTER DEPLOYMENT

Team enablement

Training for staff who will direct, correct, and audit AI employees after handover.

For you if: adoption is your bottleneck, not technology

DELIVERABLETRAINING + PLAYBOOKS

05OwnBring it in-house
05

Own your infrastructure

Run suitable models on your hardware to control high-volume costs and keep sensitive data on site.

Local AI deployment

Hardware sizing, procurement guidance, and open models tuned to your workload, run entirely on premises.

For you if: metered bills or data egress keep you up at night

DELIVERABLEON-PREM INFERENCE STACK

Hybrid model estate

Routing between local and frontier models per task: privacy and cost locally, peak capability when it pays.

For you if: you need local cost control and frontier capability

DELIVERABLEMODEL ROUTER + POLICY

Managed operations

We run what we built (monitoring, model upgrades, skill maintenance) until your team is ready to take the keys.

For you if: no in-house ML ops team (yet)

DELIVERABLESLA-BACKED OPERATIONS · QUOTED UPFRONT

START FROM ZERO

One 90-day engagement across all five stages

We run assessment through deployment with one accountable team and milestones you can hold us to. We take a maximum of two Foundation engagements at a time, so the founder remains directly involved in every one.