AI Workflow Implementation and Integration
Typical timeline: 3–8 weeks
Move one workflow from idea to working pilot.
Dot AI Consulting designs and builds focused AI workflows inside the systems your team already uses, with human review, evaluation, documentation, and ownership built in. This is a working pilot or production-ready internal system — not a proof of concept that stops at the demo.
A strong fit if this sounds familiar
- Teams with a clearly defined workflow that needs a working pilot or production-ready internal system
- Companies ready to move from a promising idea to something connected and measurable
- Product teams adding AI functionality to an existing application
- Operations teams needing integration with CRMs, document stores, databases, or internal tools
- Pilot or production-ready AI workflow built and tested
- Integrations with existing tools, APIs, and data sources
- Human review and fallback paths for reliability and safety
- Evaluation criteria and quality benchmarks
- Documentation and ownership handoff your team can maintain
What we cover together
- Scoping session to define the workflow, data sources, integrations, and success criteria
- Pilot build with the agreed toolchain, APIs, or model provider
- Integration with existing tools — CRMs, document stores, databases, internal systems
- Human review checkpoints, fallback paths, and failure handling
- Evaluation setup with quality benchmarks and test cases
- Basic monitoring and usage measurement
- Handoff documentation, ownership guide, and follow-up recommendations
- Team walkthrough and training at delivery
Workflows we build
Focused, real-world systems — not proofs of concept. Each is connected to the tools and data the team already uses.
A clear path forward
- 1
Scope and define
We agree on the workflow, input and output format, data sources, integrations required, and a measurable definition of success before work begins.
- 2
Build and integrate
The pilot is built and connected to the tools and data the workflow depends on — not a standalone prototype that requires a separate integration later.
- 3
Test and evaluate
We run the system with real inputs, establish quality benchmarks, add reliability checks, and document failure handling before handoff.
- 4
Hand off and document
You receive documentation your team can maintain, a team walkthrough, and a clear path for iteration after delivery.
What you leave with
Concrete artifacts your team can use after the engagement ends.
Built-in, not bolted on
Practical safeguards are part of the engagement — not a separate service.
- Data handling and access requirements are reviewed before the build begins
- Sensitive data is not sent to third-party tools without explicit review and approval
- Human review checkpoints are designed into every high-impact output
- Failure and fallback paths are part of the build, not an afterthought
- Quality benchmarks and test cases are established before launch
- Documentation is written so the team can maintain and modify the system without ongoing dependency
How the engagement is sized
Implementation engagements are scoped after the workflow, systems, data, integration requirements, security needs, and success measures are understood. A fixed-fee proposal is provided before work begins.
Typical first engagement
A typical implementation engagement delivers one clearly defined workflow and its required integrations. Dot AI Consulting can design and implement a bounded AI feature within an existing product. Full greenfield product development, long-term staff augmentation, and complete platform rebuilds are scoped separately or referred to an appropriate partner.
- Number of integrations and data sources involved
- Complexity of the workflow logic and decision paths
- Security and data-handling requirements
- Depth of evaluation and testing required
- Number of team members to onboard at handoff
What this engagement does not cover
- Custom software platform or product development
- Ongoing managed service or hosted operations
- Regulatory compliance certification or formal security audit
- Work dependent on data cleanup not included in the engagement
- Procurement of new software licenses or infrastructure
Required stakeholders
A focused engagement works best when the right people are available for a short interview or scoping call before work begins.
- Workflow owner who can define the inputs, outputs, success criteria, and edge cases
- IT or engineering contact for access to APIs, databases, authentication, and internal systems
- End users of the workflow — available for testing, feedback, and the final walkthrough
- Optional: data or security lead if sensitive data, PII, or compliance constraints are involved
Common questions about this engagement
Discuss this engagement
Start with a free 30-minute discovery call. Bring one workflow or business problem and we will discuss whether this engagement is the right next step.