A pitch on owning your intelligence layer instead of renting it from forty SaaS vendors.
Spend is up. The org feels busier. The model demos look incredible. And yet the actual structure of how your business decides things has not moved much.
Every quarter ships a new prototype. Almost none of it ends up running the business. The headline is the same in every intake we run.
Compressed from 200+ intake transcripts. The full board has seven. These four are load-bearing.
Forty interfaces that each know one-fortieth of the company. None of them know each other.
How your company qualifies a lead now lives inside someone else's prompt template. You do not see it, version it, or leave with it.
The model knows your business as well on day 400 as on day 1, because nothing about your operation is persisted in a place you control.
The next twelve months replicate today's tool sprawl, but with actors that run themselves.
We've shipped twelve copilots in eighteen months. None of them know each other exists. Every one of them learned our company from scratch, and then forgot.
Business logic scattered across vendors. Humans copy state between them. Every tool is an island with its own schema and politics.
Memory, goals, rules, and schemas live in one owned layer. Agents and workflows orbit it. Tools become instruments.
A durable, structured record of what your company knows, decides, and remembers.
Explicit, executable representations of how work moves through your business.
System prompts, tool grants, and policy boundaries for each agent.
Human-in-the-loop gates with scope, signers, and timeouts.
Typed structures for customers, contracts, decisions, and other business objects.
Thin, owned adapters into the SaaS you keep.
Policies, goals, and decision rules governing how the layer reasons and acts.
Continuous measurement for every agent, workflow, and decision.
Every extra SaaS layer adds hidden logic, permissions, context drift, and a place where company intelligence leaks.
The remaining tools become instruments your intelligence layer drives end-to-end.
Less software. More leverage. Less time in vendor consoles, more time setting goals.
Human drives. AI completes sentences and lookups.
Human drives. AI proposes drafts and next actions inside each tool.
Machine drives within rails. Human approves only at thresholds.
Machine runs the loop. Human sets goals and reviews outcomes.
Inventory every AI surface, locate where decision logic lives, and score workflows against the autonomy ladder.
Memory, schemas, and approvals stood up in an environment you own.
Two or three load-bearing workflows migrate to L3. Eval suites run in production.
Runbooks, eval dashboards, and extension patterns transfer to your team.
Both are services: high-trust, hands-on, owned at handover. SparkOS is not a license. It is what we build into you.
A short, fixed-scope engagement. We audit your operating layer and leave you with a Spark Map and ranked intervention targets.
End-to-end engagement. We install primitives, codify decision logic, and move 2-3 workflows into autopilot.
Your business is already a codebase. Spark makes it explicit, executable, and owned. Start with the EUR 5,000 Foundation Track.