We design, deploy, and measure AI where it actually moves the needle, governed adoption strategy, customer- or employee-facing chatbots, and RAGs on your own knowledge. For organizations tired of pilots that die in three months and teams using ChatGPT on their own with no governance or measurement.
or write to us at info@theoptimalflow.com
−90%
cost per interaction with a well-built chatbot vs. human agent
10×
team response speed with RAG on your own knowledge
3–8 wk
from diagnostic to first AI use case in production
The problem
Organizations have been investing in AI for two years and most still can't extract measurable value. Pilots that die in demo, teams using ChatGPT on their own, data invisible to the models. This is what we find when we enter.
5%
Fuente · MIT NANDA Initiative
Síntoma · 01
MIT puts the number on it unambiguously: the remaining 95% stay in "pilot purgatory": flashy demos, consumed budgets, and no change in the P&L. The problem is rarely the model; it's not having designed the use case, governance, or measurement from the start.
78%
Fuente · Microsoft Work Trend Index 2024
Síntoma · 02
Microsoft calls it "BYOAI" and it keeps growing. The CIO doesn't know what data leaves the company, what decisions are made with those answers, or how much value is generated. The whole investment in governed AI dilutes before it begins.
80%
Fuente · Grand View Research
Síntoma · 03
Policies, manuals, contracts, history, tickets: the bulk of useful knowledge lives in unstructured documents that no generic ChatGPT sees. Without RAG on your sources, AI can only answer with generalities, and it shows.
12×
Fuente · McKinsey · AI in Customer Service 2026
Síntoma · 04
McKinsey puts the number on it: $7.40 per human-agent interaction vs. $0.62 with a chatbot grounded in real knowledge and handing off to a human when appropriate. The difference isn't the technology, it's the quality of the deployment.
How we help
The stack
Each use case calls for its model: deep reasoning for analysis, cross-cutting day-to-day use, integration with the existing stack, or enterprise search across all knowledge.
Anthropic's model: deep reasoning, long context, and excellence in technical analysis, writing, and code.
Google's multimodal model, natively integrated with Workspace, Cloud, and the rest of the ecosystem.
AI embedded in Microsoft 365. Word, Excel, Outlook, Teams. The natural entry point in organizations with a Microsoft stack.
Enterprise search and RAG across your whole stack. Notion, Slack, Drive, Salesforce, GitHub. The knowledge layer that bridges silos.
A sequence proven in 200+ companies. Each phase has deliverables before moving to the next, and is developed in collaboration with your internal team.
Diagnostic
We audit existing processes and the current stack. We map bottlenecks and optimization opportunities to ensure the success of the following phases.
Planning
We define target architecture, rollout plan, roles, and metrics before getting into the weeds.
Build
We execute in short iterations with your team. We create, adapt, and integrate with your existing tools.
Rollout
We start with a test and expand after validation. We train your team so adoption feels natural.
Follow-through
We measure and listen to feedback throughout so the result truly becomes yours.
Why us
Holistic approach
We see every process as part of a whole. We act as change catalysts combining innovation, diversity, and radical honesty to build real solutions aligned with our clients' goals.
Optimization as the standard
We believe in turning complexity into intuitive systems where every gear runs naturally, maximizing the time, resources, and creativity of the people using them.
Partners, not clients
We co-create with your internal team to build tailored solutions that prioritize long-term impact over short-term wins.
Book a free intro session so we can understand where you stand and how we can help. No strings attached.
or write to us at info@theoptimalflow.com
