01
Someone needs to own the last mile
Prototypes are easy to admire. Production systems need workflow ownership, integrations, permissions, failure handling, and a rollout plan.
Boutique forward-deployed engineering for B2B SaaS
Take one important AI workflow from operating pain to production.
devology.ai gives B2B SaaS teams one accountable senior partner and a governed agentic delivery bench to discover, build, deploy, and improve AI systems in the workflows that run the business.
Production ownershipIntegrations, evals, approvals, observability, and handoff.
Focused delivery capacityAdd senior FDE capability without a permanent department.
Post-launch improvementMonitor drift, respond to regressions, and keep the workflow useful.
The problem
AI projects do not need another strategy deck.
They need an accountable technical partner who can translate an operating problem into a production system, navigate the ugly integrations, and stay close enough to improve it.
02
Your team has the problem, not the capacity
A boutique FDE partner adds focused delivery capacity without adding a permanent department.
03
Deployment is not the finish line
Evals, observability, retuning, and handoff turn a launch into a reliable capability.
The engagement model
A senior FDE partner, with a delivery bench behind it.
Choose the level of help you need—from a focused discovery sprint to an embedded deployment partner and ongoing fractional FDE support.
No benchware. No slideware. Senior judgment where it matters.Discovery sprint
Map the workflow, validate the opportunity, and build a working proof with evals from day one.
2–3 weeks · fixed scopeDeployment sprints
Build the production agent, RAG workflow, integration, UI, eval suite, observability, and handoff.
2-week delivery sprintsFractional FDE
Stay embedded after launch for drift monitoring, regression response, retuning, roadmap, and enablement.
Monthly partnershipReadiness audit
Start with a contained assessment when the workflow is promising but the right production path is not yet clear.
Low-risk entry pointThe process
Move from operating pain to production capability.
One partner keeps the work accountable. A governed agentic bench handles repeatable research, build, QA, eval, and documentation work behind the scenes.
01
Discover the workflow
Trace a real example, quantify the drag, and identify the data, systems, and approvals involved.
02
Build with evals from day one
Design the architecture, build the narrowest useful system, and test it against the failures that matter.
03
Deploy, observe, and hand off
Ship through approval gates, connect observability, document the runbook, and keep improving.
The handoff
What lands in your team’s hands.
Every engagement produces operating artifacts, not just recommendations. Your team should know what shipped, how to judge it, and who owns the next decision.
Triggers, actors, handoffs, exceptions, source systems, and the workflow owner.
Baseline, target outcome, evaluation cases, release thresholds, and open risks.
Agent, internal tool, or automation connected to the systems where the work happens.
Regression tests, failure examples, review paths, and evidence for release decisions.
How the system is monitored, escalated, updated, and handed to operators.
What to fix, measure, or expand next—and the conditions required to do it safely.
The fit
Best when the workflow is real and delivery capacity is the constraint.
Likely a good fit
- A recurring operational workflow creates measurable drag.
- You need senior delivery capacity without hiring a full team.
- A technical sponsor and operational owner can stay engaged.
- You want a safe path to production and a maintainable handoff.
Probably not the right time
- You only want an open-ended AI strategy exercise.
- There is no named workflow owner or measurable problem.
- Data access, security review, or human accountability is undefined.
- You need a free prototype before agreeing on the problem.
Start with a conversation
Discuss a deployment.
Start with the outcome you need to ship. We will work out whether that calls for a discovery sprint, deployment sprint, or ongoing fractional FDE partnership.
Talk about your workflow ↗Contact link to be configured before publishing.
Onboarding agent
Start with the workflow, not the model.
Tell us what is creating drag. The agent will help structure the problem and tell you whether a founder conversation is the right next step.
Prefer to continue with a human?Choose a teammate. Your email will open with this chat as context; review it before sending.
Do not share credentials, confidential client data, or sensitive personal information.