— The problem —
Most AI projects for SMBs never reach production.
The pattern is predictable: a developer hooks up an API, it works in a demo, and then it quietly fails in production because no one built the surrounding infrastructure — auth, rate limiting, cost controls, error handling, observability. The project gets shelved, the team loses confidence in AI, and the opportunity is wasted.
We've seen enough of these projects to know where they break. Production AI development isn't harder than demo AI — it just requires the surrounding work that most shops skip. We include it as baseline: eval suites, observability, security handoffs. Not add-ons. Not 'phase 2'. In the build.
— What we build —
Four types of AI systems, one operating standard.
Every engagement is scoped to a specific problem. We don't take open-ended retainers.
AI Agents
Automate the workflows costing your ops team the most hours.
Multi-step agents that connect to your tools, read data, take actions, and escalate what they can't handle. Built with eval pipelines and observability.
Learn about AI agents →AI Chatbots
LLM-powered bots connected to your data, not hallucinations.
Customer support bots, internal knowledge assistants, and lead qualification systems — grounded in your documentation and scoped to a specific use case.
Learn about AI chatbots →AI Integrations
AI inside your CRM, helpdesk, and internal tools.
We wire OpenAI and Claude into your existing stack via API. No replacement required. Auth, security, and observability included as baseline.
Learn about AI integrations →AI Strategy
Decide what to build before you spend anything building it.
Fixed-scope advisory engagements: AI readiness review, build-vs-buy decisions, architecture review. Starts with the $497 audit.
Learn about AI consulting →— How we work —
The operating model that makes it ship.
Four principles that separate production AI from demos.
01
Fixed scope
We define requirements, acceptance criteria, and timeline before any code is written. You know the price, the delivery date, and exactly what you'll receive — before you pay anything.
02
Eval before ship
Every system we build includes a test suite that runs against real inputs before deployment. If the system fails any eval, it doesn't ship. You get the eval results as part of the handoff.
03
Observability included
LLM call logs, cost per call, latency, error rates, and drift detection — all set up before handoff. Your team can see what the AI is doing without reading code.
04
Outcome guarantee
On ClearShip projects, acceptance criteria are a legal contract. If we miss a criterion at delivery, you get a full refund. This is how we stay honest about scope during build.
— How we compare —
Fixed scope. No surprise invoices.
— Built for —
Right for some. Not for everyone.
Built for
- $1M–$15M businesses with real digital operations
- A specific workflow costing your team 5+ hours/week
- At least one technical contact available for handoff
- Ready to run AI in production, not just experiment
Not a fit
- Pre-revenue or <$1M — the ROI math doesn't hold
- Projects with undefined requirements or moving scope
- Businesses that need ongoing AI management post-delivery
- Consumer apps, generative media, or regulated industries
Find the right starting point.
Most clients start with the $497 AI Profit Leak Audit — it identifies the highest-ROI opportunity in your operations and produces a spec we can build from. If you already know what you want, book a call directly.
— Common questions —
Quick answers.
What is AI development?+
AI development is the process of building software systems that use artificial intelligence — specifically large language models (LLMs), machine learning, or automation — to solve business problems. For most SMBs, this means one of three things: AI agents that automate multi-step workflows, chatbots that handle customer or internal queries, or LLM integrations that add AI features to existing tools. The goal is always a production system that works reliably, not a prototype.
How much does AI development cost for a small business?+
The range is wide — from $3,000 for a simple workflow automation to $40,000+ for a multi-agent system with full observability. Most first projects for $1M–$15M businesses land in the $5,000–$20,000 range. The most important thing is scoping: a well-scoped AI project is typically 2–5x cheaper than an open-ended one. We start with the $497 AI Profit Leak Audit to identify your highest-ROI opportunity before any development starts.
What kinds of AI development do you do?+
We build AI agents (multi-step workflow automation), AI chatbots (LLM-powered conversational systems), AI integrations (adding LLM features to your CRM, helpdesk, or internal tools), and custom AI software for specific operations problems. We don't do consumer apps, generative media tools, or projects where the requirements aren't defined.
How long does AI development take?+
Simple integrations and chatbots take 2–4 weeks. AI agents with multiple tools and integrations take 4–8 weeks. More complex multi-agent systems with custom observability take 8–12 weeks. All timelines are fixed at scoping — you know your delivery date before we write any code.
Do I need to know how AI works to hire you?+
No. You need to know your business problem — what's costing your team the most time, what's breaking down in your operations, what you wish happened automatically. We translate that into an AI system. The technical design (model selection, architecture, tool use, evaluation) is our job.
What's the difference between AI development and AI consulting?+
Consulting is about deciding what to build. Development is building it. In practice, good AI development requires strategic judgment, and good AI strategy requires technical depth — so the line blurs. We do both: our audit service identifies the highest-leverage opportunity, and our development service ships it to production.
How do you make sure the AI system actually works?+
Every project includes an eval suite — a set of test cases that run before deployment to verify the system behaves correctly on representative inputs. We also set up observability (logging, cost tracking, drift detection) so you can monitor the system after it's live. We don't ship systems we can't measure.
— Ready to start? —
Build the system. See what it saves.
Most clients are in production within 8 weeks. Start with the audit to find the right workflow, or book a call if you already know what you want to build.