Services built to ship, not to decorate a roadmap.
AI transformation from a Chicago studio that ships. Three services, one standard: work should leave the building as a product, a decision framework, or a running system.
SaaS product studio
We conceive, design, build, and launch SaaS products, including for founders who need a full studio partner.
- Concept and positioning
- What the product is for, who it serves, what it refuses to be.
- Product design
- Flows, information architecture, interface clarity.
- Engineering
- SaaS foundations, core workflows, integrations.
- Launch
- Shipping to real users with the operational pieces a product needs to stay alive.
When this is the right lane
You need a product that does not exist yet. You have domain insight and need a team that can turn it into software. You want studio ownership of quality, not a rotating cast of contractors.
What success looks like
A live product with a clear value path, not a prototype trapped in a staging environment.
AI consulting
We help businesses adopt AI properly: strategy, readiness, use-case selection, governance, and adoption.
- Strategy
- Where AI creates durable advantage in your operating model, and where it is noise.
- Readiness
- Data, process, talent, and risk posture. We separate "interesting demo" from "ready to run."
- Use-case selection
- We rank opportunities by value, feasibility, and blast radius. Not every workflow deserves a model.
- Governance
- Policies, evaluation habits, human oversight, and accountability so AI does not become an unowned liability.
- Adoption
- Rollout plans that operators will actually use. Training, change paths, and feedback loops that keep systems honest after week one.
When this is the right lane
Leadership wants AI without theater. You need a map before a build. You need governance that matches how your company already manages risk.
AI engineering
We ship production AI systems: agents, LLM integrations, automation, and evaluation.
- Agents
- Task-scoped agents with tools, memory boundaries, and failure modes you can explain.
- LLM integrations
- Models wired into real products and internal systems, with latency, cost, and quality treated as first-class constraints.
- Automation
- Workflows that remove manual drag without hiding decisions inside a black box.
- Evaluation
- Tests, traces, and quality bars so "it works in the demo" is not the release criteria.
When this is the right lane
You already know the use case. You need it in production, monitored, and maintainable.
How engagements typically run
- 1
Diagnostic
Scope, constraints, and success definition.
- 2
Plan
Architecture or product plan with clear build boundaries.
- 3
Build or advise
Studio delivery, consulting artifacts, or engineering implementation.
- 4
Handoff
Documentation, operating notes, and ownership transfer so the work survives without us.
Exact shape depends on the service line. The sequence does not: clarity first, then delivery.
What we will not do
- Pitch AI as magic.
- Invent case studies or borrowed glory.
- Optimize for billable ambiguity.
- Ship systems we would not run ourselves.
Our own products keep that standard concrete. See the products we own.
Questions
What is the difference between DRYHURST's AI consulting and AI engineering?
AI consulting covers strategy, readiness, use-case selection, governance, and adoption: what to do, why, and how the organization should run it. AI engineering covers building production systems: agents, LLM integrations, automation, and evaluation. Many clients use both in sequence; consulting defines the target, engineering ships it.
Do you only work with early-stage founders?
No. We work with founders who need a SaaS product built, and with CTOs and operations leaders at SMBs and mid-market companies who need AI adopted and shipped properly. Fit is driven by problem clarity and willingness to ship, not by stage label alone.
Can DRYHURST build a full SaaS product from idea to launch?
Yes. The SaaS product studio conceives, designs, builds, and launches products, including for founders. Engagements typically move from concept and positioning through design and engineering into a live launch, with handoff materials so your team can operate what ships.
What proof points does DRYHURST use if you do not publish client case studies?
We point to products we own and operate: Invoice My Clients (invoicemyclients.com), OnDue (ondue.ai), and Jumpstart (jumpstart.co). Those products reflect the same studio and AI practices we bring to external work.
Where is DRYHURST based?
Chicago, Illinois. DRYHURST is a Chicago AI transformation agency and product studio. We work with companies across Chicagoland and with teams outside the city.
How should we prepare for a first conversation?
Send a short brief: the outcome you need (product, AI program, or production system), current constraints (timeline, stack, risk), and what "done" means in concrete terms. We respond with fit, likely service line, and proposed next steps. Start on the contact page.
Want to see how we think before you write to us? Read our articles on applied AI.
Start with a short brief.
If you are choosing between building a SaaS product, standing up an AI program, or shipping a production system, tell us. We will say which service fits, and which does not.
Start a conversation