Enterprise AI Solutions
AI and automation, assembled from the process.
Agentforce when the work lives in Salesforce. A custom stack when it does not. Data readiness first. We will tell you no if the problem is not an agent problem. The first week is in the org, reading what already exists.
Certified Partner since 2010 · MVP Hall of Fame · 200+ agents in production · UAE and US desks
The week
What is actually stuck.
We assemble the runtime from the use case: Agentforce, Claude / OpenAI / Gemini, ADK or CrewAI, memory, and MCP. Einstein recommends. Agentforce acts. They are not the same product. If you need the decision page, start at Agentforce vs custom.
Manual Process Bottlenecks
Your team burns the day on the same repeated job. That job is your first agent. You do not need twenty.
Data Silos & Fragmentation
Disconnected systems mean the agent will guess. Data readiness first.
Decision-Making Delays
Lack of real-time intelligence causes missed opportunities and reactive rather than predictive business strategies.
Scalability Constraints
Manual processes cannot scale with business growth, creating operational bottlenecks and increased error rates.
Competitive Disadvantage
A demo org is not a production method. Competitors who shipped one process will beat a slide deck.
ROI Uncertainty
If you cannot name the process and the reviewer, you cannot measure the agent.
The work
What we put in.
Sequence
How the week runs.
- 01AI Readiness Assessment2 weeks · Evaluate data quality and system integration readiness Identify high-ROI automation opportunities Assess organizational AI maturity and skill gaps Define success metrics and ROI targets
- 02Pilot Implementation4-6 weeks · Deploy proof-of-concept for selected use case Configure Einstein AI or Agentforce for quick wins Measure initial performance and gather feedback Refine models based on real-world results
- 03Enterprise Rollout3-4 months · Scale successful pilots across departments Integrate AI with existing business systems Implement governance and ethical AI frameworks Deploy monitoring and optimization tools
- 04Continuous LearningOngoing · Fine-tune models with production data Expand automation to new processes Upskill teams through AI literacy programs Track ROI and optimization opportunities
The honest no
When we are the wrong partner.
The honest no: if the work is a software factory with a named delivery date, we are the wrong partner.
Answers
What we actually say.
The same questions, answered without a brochure.
- What does AI automation deliver?
- We will not invent a percentage. Send the process. We come back with a stack, a sequence, or an honest no.
- Does Mindcat implement Einstein and Agentforce?
- Einstein recommends. Agentforce acts. We implement the runtime the org can actually support, with Data Cloud or Knowledge when the context layer needs it.
- How long does an AI automation project take?
- A named first process can launch in weeks. An unread programme cannot. Send the process.
The brief