FAQ
Questions worth answering before the build.
Plain answers about scope, delivery, data, cost, and what AI can realistically do.
What does CortexLane build?+
We build AI agents and automation, generative-AI and LLM apps, custom AI products, data and MLOps infrastructure, AI features for existing software, and the web and mobile products around them. AI is our main focus; the rest is there to ship it.
Who do you work with?+
Startups, scale-ups, and teams across industries—SaaS, fintech, healthcare, e-commerce, logistics, and more—who need practical AI engineering and product work, from a first automation to a full product.
Who will actually do the work?+
Senior engineers, with a named technical lead involved in your project. A senior engineer reviews AI-generated code before it ships, so you are never handed unreviewed output.
How does an engagement start?+
We begin with a short call, clarify the business outcome, and propose the smallest useful first phase with milestones and a delivery range before work starts.
How long does a project take?+
It depends on scope and integration risk. After discovery we give you milestones and a delivery range. Most first releases land in weeks, not months.
What does progress look like early on?+
We agree what success means during discovery and show working software with a demo every week, so you can judge progress on evidence rather than status reports.
How do you check quality and handle mistakes?+
We build evaluation sets from real examples and track accuracy, latency, and cost. Sensitive actions get human review, guardrails, and safe failure states—so a wrong output is caught, not shipped.
How much does it cost?+
Every engagement is scoped around the outcome and risk, with fixed-price, dedicated-team, and partnership options. Tell us your goals and we give a transparent estimate before any work begins.
What are the ongoing costs after launch?+
Beyond our fee, AI features carry model/API and infrastructure costs. We estimate these up front and design to keep them visible and controllable, so there are no surprises later.
Do we own the code, models, and IP?+
Yes. You own the source code, designs, and IP we build for you—including AI-generated code—handed over with documentation so your team can take it forward.
How do you protect our data?+
We use least-privilege access, keep environments separate, avoid training on client data by default, and document retention and deletion. NDAs are standard.
Can you work with our developers and tools?+
Yes. We can deliver independently or embed in your product and engineering process, and we choose models and tools by quality, privacy, latency, cost, and portability—not vendor loyalty.
Do you guarantee model accuracy?+
No. We define testable quality targets, evaluation, and controls, and design safe failure states. We never promise perfect outputs.
What happens after launch?+
We can hand over the system, support it through a retainer, or provide a dedicated engineer for continued improvement.