Tooling
Connected systems
We connect AI to the systems your teams already use: governed agents, orchestrated workflows, and permissioned integrations — so capability scales without losing control.
AI that runs inside your company.
We design and implement how your organization captures, governs, and applies institutional knowledge — so AI works inside your tools, workflows, and standards.
What we do
Source Craft builds end-to-end AI inside your organization — not isolated chat tools, but a connected system across tooling, knowledge, engineering, and how work actually flows.
Tooling
We connect AI to the systems your teams already use: governed agents, orchestrated workflows, and permissioned integrations — so capability scales without losing control.
Knowledge
We structure what your company knows: policies, playbooks, documentation, and domain expertise in a form AI can use reliably — with privacy tiers your Legal team can defend.
Workflow
We map how work moves through departments, where human judgment belongs, and where automation earns its place — then ship it to production with clear ownership.
Engineering
Your internal systems decide what AI can touch. We make them integration-ready: permissioned APIs, layered architecture, and senior engineering for new builds.
The system
One integrated stack — from tooling to engineering.
Connected systems, governed agents, and permissioned integrations your teams already use.
Policies, playbooks, and expertise — structured so AI can use it, with privacy tiers Legal can defend.
How work moves, where humans decide, and what ships to production with clear ownership.
Integration-ready software, APIs, and custom builds — extended in pieces or from scratch.
Programs
Seven entry points. One integrated path. Pick where you are stuck — we build from there.
Full journey
AI is chaotic org-wide — no owner, no policy, no production wins, board is asking questions.
Ungoverned scattered AI. Shadow audit, governance pack, one department to production, then a scale playbook.
The complete top-down path. Everything else is a door into this — funded phase by phase.
Diagnostic
You bought Copilot or ChatGPT and productivity stayed flat. Teams blame the tool.
The process is the bottleneck. We shadow workflows and hand you a ranked fix list — where AI helps vs where the process itself is broken.
Diagnoses how work actually moves — handoffs, duplicate data entry, and email-driven work. Not a knowledge or security audit.
Diagnostic
People ask AI about your company and get generic answers. Knowledge lives in a dozen places.
We test real employee questions against what you have today and design the fix — including private, on-premise options.
What AI can know about your company — and why it still gives generic answers. Maps your knowledge and why AI cannot find it.
Legal-first
Legal or security blocked cloud AI. Shadow usage continues. Nobody owns the architecture.
Local models, clear data boundaries, usage governance — a system Legal can defend and engineering can maintain.
Starts from risk, not productivity. Makes AI permissible first — then useful.
Opus · product
You need a private knowledge platform — not another chatbot. Legal requires on-prem or strict data control.
Licensed Opus on your infrastructure: ingest, access control, local AI, training. Your data stays yours.
The knowledge layer. Often follows KB Audit or sits inside Foundation Phase 3. Product + implementation.
Platform · reporting
AI work is happening but leadership cannot see it. No dept rollups, no throughput view, no exec reporting.
Org-wide AI operations: department map, live activity, session history, manager rollups, executive digests.
The visibility layer. Where execs and managers actually watch orchestration happen.
Engineering
You run internal software, ERPs, or custom systems — and AI stalls because none of it can connect.
Integration-readiness audit, permissioned API layers, layered architecture — and custom development where the gap is real.
Engineering before AI. Extend in focused pieces, split monoliths into layers, or build new systems from scratch.
What each engagement actually includes — from start to finish.
| What the engagement covers | Process Gap | Next-level | KB Audit | Opus | Secure AI | Engineering | Foundation |
|---|---|---|---|---|---|---|---|
| Shadow AI audit and process mapping | ✓ | · | ✓ | · | ✓ | ✓ | ✓ |
| Workflow redesign and automation | ✓ | · | · | · | · | · | ✓ |
| Org-wide AI operations and visibility | · | ✓ | · | · | · | · | ✓ |
| AI orchestration model and playbooks | · | ✓ | · | · | · | · | ✓ |
| Knowledge base structuring and findability | · | · | ✓ | ✓ | · | · | ✓ |
| Licensed Opus on your infrastructure | · | · | · | ✓ | · | · | ✓ |
| Local models and data boundaries | · | · | · | ✓ | ✓ | · | ✓ |
| Legal and security architecture | · | · | · | · | ✓ | · | ✓ |
| Internal software and ERP integration readiness | · | · | · | · | · | ✓ | ✓ |
| Permissioned APIs for internal tools and prototypes | · | · | · | · | · | ✓ | ✓ |
| Layered architecture AI can extend + custom development | · | · | · | · | · | ✓ | ✓ |
| Documentation and training | · | · | ✓ | ✓ | ✓ | ✓ | ✓ |
| Governance pack and playbooks | · | · | · | · | · | · | ✓ |
| Department to production rollout | · | · | · | · | · | · | ✓ |
The stack
Orchestration, knowledge, visibility, and engineering — built to work as one system.
01
Operating model
How work flows: priority, domain ownership, versioned playbooks, and human approval where it matters.
02
Knowledge
Institutional memory on your infrastructure — docs, policies, and context AI can use, with privacy tiers Legal can sign off on.
03
Visibility
Org-wide command layer: department hierarchy, live activity, manager rollups, and executive digests.
04
Engineering
Integration-ready architecture, permissioned APIs, and custom development — in pieces or from scratch.
Quick guide
YOU?
“No AI owner and Legal is nervous.”
Foundation Program →“We bought the tools. Nothing changed.”
Process Gap Audit →“AI does not know our company.”
KB Intelligence Audit →“Legal will not approve cloud AI.”
Secure AI Architecture →“We need a private knowledge platform.”
Opus →“Leadership cannot see what is happening.”
Next-level AI →“Our internal software cannot support AI.”
AI-Ready Engineering →Contact
Tell us where you are stuck. We will map the right entry point.