Your data changes. Your customers' questions are unpredictable. Every context fix risks breaking something else. Inventive makes customer-facing AI reliable across all of it — every data source, every account, measurably better every week.
The Inventive difference
The rest of the industry gives you a starting point and wishes you luck. Inventive is built for what comes after: testing, measuring, and improving your AI in production.
Measure it. Prove it. Drill into it.
Know exactly how your AI is performing — across every account, data source, and question type.
Not a gut feeling, but a score you can report to your board.
Test across accounts
Automated tests run across a representative set of your customer accounts — different geographies, data scales, business types. Quality isn't sampled. It's measured.
Deploy safe upgrades
A fix for one customer type is regression-tested across others before it reaches any customer. Nothing ships that breaks what already works.
Drill into scores
Inspect quality by account, data source, and question type. See exactly where your AI is strong, where it's improving, and where it needs attention.
Gets better every week, and keeps you in control
Context for customer-facing AI is never "done." Your data models change, new customer accounts bring new edge cases, LLMs evolve, and questions you never anticipated surface daily. Maintaining quality manually means rewriting context, hoping you didn't break something, and having no way to know until a customer complains.
Inventive replaces that cycle. When a customer flags an issue or the system detects a problem, it diagnoses the root cause, proposes a fix with auto-generated tests, and routes it to your team for approval. Once approved, it deploys without regressions — and notifies the customer who raised it.
Embedded in your SaaS product
Option 1: A contextual copilot or full-page experience — your customers get AI help right where they're already working.
White-labeled via hosted portal
Option 2: Your AI, your brand but in a standalone hosted app customized to match your company's brand.
Headless — behind your existing AI
Option 3: Any of your existing AI can call Inventive via MCP for analytics and actions, with our quality and learning systems.
1
Connect
Sits on top of your existing BI semantic layer — Looker, Omni, or Cube. No new infrastructure.
2
Configure
Branding, policies, domain knowledge, guardrails, and actions — first-party and third-party. We help you define representative test accounts for your customer base.
3
Ship and start learning
Launch with a quality score from day one. The learning system starts improving from real usage immediately — your AI gets measurably better every week with near-zero effort from your team.
Full control. No black box.
Your data, governed
Queries your governed data models in near real-time for accurate, fresh results without hallucinations. All transformations, uploads, and LLM knowledge are clearly attributed, explained, and inspectable.
Your context, enforced
Policies, guardrails, branding, and permissions — configurable per account and per user role. Actions are always proposed to the end user for approval. The AI drafts; the human decides.
Your interactions, auditable
Every response is logged, traceable, and inspectable — from the data that produced it to the logic that shaped it.
Your customers, understood
See what your customers are asking, how often, and emerging themes. The system suggests improvements to your data, product, or AI context — automatically.
