Frequently asked questions

Not really—Sertainly doesn't introduce new complexity, it exposes complexity that already exists.

Most organizations already have the same decision logic duplicated across APIs, UIs, workflows, and integrations. That logic inevitably drifts, creating inconsistencies and risk.

Sertainly makes those decisions explicit, centralized, and governable.

Anywhere a wrong decision has real consequences:

• Compliance and regulatory environments
• Pricing, eligibility, underwriting
• Multi-channel systems (API, UI, agents)
• Situations requiring auditability

If you ever need to answer “Why did this decision happen?”, you already need this.

Traditional tools like Drools or Pega focus on executing decisions within a specific system.

Sertainly defines decisions as a portable, governed source of truth across systems.

It's not just execution—it's alignment:

• Across runtimes
• Across teams
• Across channels

It doesn't require a full migration.

Sertainly can be introduced incrementally:

• Start with a single high-risk decision area
• Run in parallel (“shadow mode”)
• Compare outputs with existing logic

There's no need to disrupt existing systems upfront.

Sertainly creates a shared contract across functions:

• Engineering → execution
• Product → intent
• Compliance → constraints

Rather than creating confusion, it aligns ownership around a single source of truth.

Sertainly is not inherently a runtime bottleneck.

Policies can be precompiled, cached, and executed locally or as a service.

This is fundamentally a distribution and evaluation problem, not a latency problem.

Sertainly delivers value in three areas:

• Risk reduction — prevent inconsistent decisions, reduce compliance exposure
• Speed — change logic once, propagate everywhere; reduce regression testing
• Leverage — safely enable automation, agents, and AI

In many cases, it pays for itself by preventing a single bad decision at scale.

AI generates decisions—but it doesn't guarantee they are allowed.

Sertainly ensures decisions are compliant, consistent, and controlled.

AI without policy introduces risk. Policy without AI limits adaptability. Modern systems require both.

The opposite. As AI becomes more powerful, the need for explicit governance increases — more decisions are made, faster, and with less human oversight.

Sertainly ensures those decisions remain bounded and accountable.

Policies inside models are opaque, non-deterministic, and difficult to audit or version.

Sertainly keeps policy explicit, testable, and enforceable outside the model.

Agents still need a source of truth. Without explicit policy, agents behave inconsistently, constraints drift, and outcomes become unpredictable.

Sertainly provides the shared policy layer that agents rely on.

No—this is about enabling bounded adaptability.

AI explores possibilities. Sertainly defines what is allowed. This combination enables flexibility without losing control.

Even perfect models don't replace business intent. Organizations still need to define strategy, risk tolerance, and compliance rules.

Sertainly expresses that intent explicitly and consistently.

No—this follows a clear industry pattern toward declarative systems:

• Infrastructure → Terraform
• APIs → contract-driven design
• Data → governed schemas

Decisions are the next layer to become declarative and governed.

Vendors like OpenAI or Anthropic can provide general guardrails. But they cannot define your business rules, your compliance requirements, or your risk tolerance.

That's Sertainly's job.