SaaS sold you a platform you couldn’t build, wrapped around business logic you couldn’t control.
AI unbundles the two. Own the logic. Buy the guarantees.
Based on the Kognitos position paper by Binny Gill, Founder & CEO
One product had to fit thousands of companies, so your process became settings, and whole ecosystems of administrators and consultants grew up to finish the logic the menus left out. Now a builder can describe what a process should do and have working logic in hours, not a quarter. Logic is where a company’s differentiation lives, so it should be yours.
Accept small freight differences from trusted vendors. Ask the buyer about everything else.
Receive and match
Handle the difference
Point solutions and AI-flavored SaaS put your logic back in someone else’s model and menus, now with a chat window on top. That isn’t owning it.
Coding agents can write much of a platform’s code. They don’t carry the pager, sit through the audit, or keep connectors alive as other vendors change their APIs. Here is what each guarantee asks of you every year, from running the Kognitos platform.
| Guarantee | What you own, every year |
|---|---|
| Run it | |
| Deployment and environmentsCloud accounts, Kubernetes, CI/CD, environment promotion, rollback | Upgrades, cluster maintenance, release engineering |
| Scaling and performanceAutoscaling, queues, back-pressure, load and soak testing | Capacity planning, performance regressions |
| Reliability and SLAsRetries, failover, idempotency, incident response, status reporting | 24/7 on-call, incident reviews, SLA reporting |
| Orchestration and stateLong-running runs, scheduling, pause and resume, durable state | Stuck-run triage, migrations of in-flight state |
| Trust it | |
| SecurityAuthentication, authorization, secrets, encryption, tenant isolation | Patching, penetration tests, vulnerability response |
| Governance and permissionsRoles, approvals, change control, applicability scopes | Access reviews, policy changes |
| Audit and replayDecision records, versioned rules, replay of past runs | Evidence requests, retention, auditor walkthroughs |
| ComplianceSOC 2, HIPAA, ISO 27001 controls and evidence | Annual audits, control testing, remediation |
| See it | |
| Logging, metrics, and monitoringStructured logs, metrics, tracing, alerting, dashboards | Alert tuning, observability costs |
| Do the work | |
| ConnectorsERPs, email, documents, databases, APIs | API changes on every connected system |
| Document understandingExtraction from invoices, emails, PDFs, scans | Model updates, new document types |
| Exception handling with peoplePause, ask, review queues, guidance, resume from the paused step | Workbench operations, reviewer tooling |
| Model management and evaluationsModel routing, prompt and model versions, regression and drift checks | Model upgrades, evaluation suites, inference cost control |
| Authoring, versioning, and the logic runtimeWriting logic in English, drafts, publish, rollback, the interpreter | Language and runtime evolution |
Every company that wants AI to run real processes picks one of these, whether it decides explicitly or not. Only one keeps your builders on the logic without handing your CIO and CFO a platform team.
The vendor’s logic, configured through menus, on the vendor’s platform.
Fast and reliable. Your process bends to the product.
Your logic, on a platform your team builds and runs.
Full control, and a platform company you didn’t mean to start.
Your logic, written in a form the business can read, on guarantees you buy.
Builders build what matters. One failure mode to test for: a platform that quietly constrains the logic.
Sometimes the answer is yes. It only makes sense if every answer is yes.
Answer the four questions.
Building the platform only makes sense if every answer is yes.
Run them through the same test: does the platform leave your logic unspecified, and carry the guarantees underneath?
Good at: routine glue across Microsoft 365, approvals, notifications.
Against the test: the logic lives in the designer’s boxes and expressions, configuration again, strained by exception-heavy, auditable work.
Good at: conversation, Microsoft 365 grounding, fast agents.
Against the test: a model plans the control flow at run time. Its own architecture guidance recommends enforcing business invariants in deterministic logic as well.
Good at: rules that must run the same way every time, exceptions resolved by people, audit and replay.
Works with them: Kognitos automations can be called from Copilot Studio.
Not as software people buy. What is dying is the bundle: the assumption that to get a reliable platform you must also accept a vendor's version of your business logic. AI makes the logic cheap to build, so companies will own more of it and buy the platform underneath.
Build the business logic, because it encodes how your company works and should be yours. Buy the platform it runs on: deployment, scaling, security, governance, audit, monitoring, and SLAs. Avoid point solutions that encode your logic in their own menus.
They can write much of the code, quickly. They can't carry the on-call rotation, sit through the SOC 2 audit, patch vulnerabilities, keep connectors working as APIs change, or explain old decisions to an auditor. Those recurring costs are people costs, not token costs.
Anything that isn't your business and has to be correct every day: the runtime, scaling, security, compliance evidence, audit and replay, and connectors to systems that change underneath you.
They are good at conversation, Microsoft 365 grounding, and routine flows. Business logic that must run the same way every time, with exceptions handled by people and a replayable record, needs a platform built for it. They work together: Kognitos automations can be called from Copilot Studio.
One that specifies everything SaaS used to carry and constrains nothing about your logic. Any rule can be expressed fully, the business can read it, it runs deterministically where it matters, and exceptions are resolved by people. Kognitos does this with English as Code.
When the platform is your product, when you already run a platform team at scale, or when a constraint no vendor can meet forces your hand. Otherwise it means entering a business you didn't plan to be in, for as long as the logic on top of it runs.
With coding agents, writing the code is the smaller part. The larger, recurring cost is supporting every platform guarantee in-house: on-call, security and compliance, connectors, and model operations, for as long as the logic runs.
The full argument: what SaaS really sold, what AI changes and what it doesn’t, what owning a platform really costs, and the questions to ask before you build.