The usual SaaS with an AI bolt-on
Multiple tools solving narrow problems, each with their own AI. The same subscriptions you were already paying for, with a new label on the box.
AI Design & Deployment
The AI everyone is selling you doesn’t know your business.
Inaltum builds AI into the way your business already delivers for its customers, starting from what has to get done and working backwards. What you end up with is a foundation layer AI customized to your business: your deliverables, your workflows, your people guiding it.
What everyone else is selling
Big brand AI rented by the seat
General-purpose AI, priced per person, every month. Trained on the world’s data. Built for everyone and therefore for no one.
Task automations supercharged by AI
You send them the tasks and SOPs, they string together tools and AI capabilities to help your team complete them more rapidly.
The harder problem isn’t the technology.
Everyone in your business sits at a different point on the adoption curve, and some of them are fearful that AI adoption ends their job. You can’t deploy AI into a room that’s bracing against it.
So we start somewhere else entirely: one-on-one conversations with your team members to identify what gives them the most heartache and show them how to fix it with AI.
The Case for Learning
Everything AI makes starts with a human.
There’s a loop behind every AI output, and a person sits at the top of it. What comes out the far end is set by the quality of who’s speaking into it.
Human PromptsA person sets the intent.
What’s actually inside a human prompt?
- Genius
- Instinct
- Experiential knowledge
- Tacit knowledge
- Wisdom
- Insight
- Nonverbal communication
- Bias perception
- Relational knowledge
- Understanding
- Intuition
AI is generally right. Humans craft solutions that connect.
You know a human-crafted solution by the reaction it gets.
- “Awe-inducing.”
- “Gives me tingles.”
- “Inspiring.”
- “Eyes light up.”
- “That’s right.”
We can now speak products and services into existence. Inaltum helps founders and their teams find the language to shape what they need.
The Org Chart Reframe
It’s time to reimagine the org chart-driven way that work has always been done.
Until now, businesses had to divide work by seniority and specialization because that’s how people scale. However, when AI sits at the foundation of a business, it can flow work easily into and out of the hands of the right people at the right time.
- Old way
- Duties are organized around what humans can do. Time served becomes knowledge, knowledge becomes seniority, and the org chart is the map of who’s allowed to do what.
- New way
- You name the objective, then collaborate with AI to build the workflow that meets it. Every step exists to serve the workflow, whether a human or an AI performs it.
Objective Create and execute a legal agreement with a new client.
What to notice. One deliverable flowing through four different levels of the org chart. No single role owns it, and the project isn’t constrained to deterministic task assignments and triggers. AI flows the work to the right people at the right time and collaborates with them along the way.
The reframe follows Alex Hormozi’s thinking on how AI reorganizes a business.
Insights Based on Flows
Five things follow from that, and we build against all five.
These are the rules we work by when we map your business. They decide what gets built, and in what order.
Role-agnostic by design
A workflow can draw on people at very different levels and specializations, because it answers to the objective and not to the org chart.
Clear objective, defined process
Workflows exist to produce a deliverable for a client, which means they can’t be spun up or wound down ad hoc.
Is“Draft and obtain signatures on a new client agreement.”
Is not“Grow the business by 10% this year.”
Context is king
The AI needs line of sight on the objective, the SOPs, prior examples, the role it plays, and how it will know it succeeded.
Fix the starting frame
The question isn’t how AI could do an individual employee’s tasks faster. The question is what we need to deliver to our clients.
AI will reorganize businesses
Roles get built around workflows, instead of workflows getting built around how people fill their roles.
The Build Loop
This is how we build a workflow.
Every workflow goes through the same three stages, and the loop runs until the work comes back right. Nothing goes live because it’s finished on a timeline. It goes live because it’s verified.
STAGE 01
Gather context
Tell it everything a new hire would need.
- Define the role of the agent.
- Define the objective.
- Define the relevant parties — who, what and why — in great detail.
- Provide the SOP, step by step.
- Identify and explain the reference materials.
- Tell it when to bring a human into the loop.
- Identify the output: document type, storage location, and so on.
- Ask the AI to confirm all of the above.
STAGE 02
Take action
It works. You watch the path it takes.
The agent goes to work. Expect it to ask permission before it reaches for anything new. Watch which tools it calls and which items it is working through, and make sure it is on the right track before it gets far.
STAGE 03
Verify work
You check the output before it counts.
- Review the final product.
- Visually check the critical details.
- Spot check the non-critical details.
- Confirm the output format is correct.
- Confirm the output location is correct.
- Provide feedback on the final output.
Where it goes
Every trip through the loop moves one workflow a rung higher.
The build loop is adapted from Anthropic’s guidance on building agents. The four levels are adapted from Notion’s AI Transformation Model.
Secure AI
Secure AI for highly regulated industries.
If a data leak would be an existential event for your business, a policy is not an architecture. For these engagements we work with specialist providers who supply the secure environment and the model. What happens inside that box is ours: we shape it around your proprietary data, insights, and workflows.
A wrapper is not a model.
Skills, projects and custom GPTs all reason inside a general model’s frame. They still hallucinate, and they still infer from material that has nothing to do with your business. What removes that is a model working inside your material and nothing else.
Zero retention is a storage promise, not a compute one.
Zero data retention and SOC 2 describe what happens to your data at rest. Every request still leaves that store and is processed on GPUs. Where those GPUs are shared, that is the exposure nobody puts on the datasheet.
Inaltum is proud to partner with specialist providers, including bolde.
Where to start
AI deployment starts on the whiteboard.
We begin on a whiteboard, not in a software demo. Bring what’s in your head, we’ll pressure-test it together, and you’ll leave with a vision and a plan for making AI the foundation of your business.