Technology and Data
Experience spanning software development, databases, data quality, business intelligence, systems integration, and technology operations.
Practical AI strategy, automation, and solution planning
I help organizations turn AI ideas into working systems, automated workflows, and practical business results.
Drawing on experience across software, databases, data, telecommunications, consulting, executive leadership, and entrepreneurship, I help organizations identify valuable AI opportunities and turn them into structured, usable solutions.
Founder of Anunnaki Technology Solutions LLC • Software and database background • Executive leadership • AI-assisted product development
Experience behind the work
Technical depth, executive perspective, and structured delivery.
Executive Leadership
Leadership experience connecting organizational priorities, technology decisions, stakeholders, risk, and operational execution.
Structured Delivery
A documentation-first approach covering requirements, workflows, architecture, acceptance criteria, testing, and implementation planning.
Founder Perspective
Hands-on experience shaping AI, automation, media, education, and community-platform initiatives from concept through active development.
Start with the business problem
You do not need another AI tool. You need clarity about what is worth changing.
Many organizations feel pressure to adopt AI but are unsure which problems are worth solving, whether their data is ready, or how new workflows will affect employees and customers. I begin with the current business process—not a preferred technology—and help identify improvements that are practical, valuable, and supportable.
- Repetitive work consumes staff time but remains undocumented.
- Customer inquiries, bookings, and follow-up may depend on disconnected tools.
- Business data exists, but quality, ownership, and reporting remain unclear.
- AI experiments occur without reusable standards or human-review controls.
Consulting services
From unclear opportunity to structured implementation.
Engagements can begin with assessment and planning or progress into workflow design, product definition, prototyping, testing, documentation, and adoption support.
01Assess
AI Strategy and Readiness
Clarify where AI may create value, what must be improved first, and which opportunities deserve priority.
- Readiness assessment
- Opportunity inventory
- Prioritization matrix
- Implementation roadmap
02Design
Workflow Automation
Document current processes, identify delays and repetitive work, and design practical future-state workflows.
- Current-state workflow
- Pain-point analysis
- Automation opportunities
- Future-state design
03Build
AI-Powered Customer Intake
Plan connected workflows for inquiries, leads, bookings, messaging, notifications, and customer follow-up.
- Intake assessment
- Lead-routing plan
- Booking requirements
- Prototype roadmap
04Understand
Data and Business Intelligence
Improve the structure, quality, reporting, and usefulness of operational data for better decision-making.
- Data assessment
- KPI definitions
- Reporting requirements
- Dashboard plan
05Standardize
Generative AI Workflows
Replace inconsistent prompting with documented inputs, reusable templates, review criteria, and human oversight.
- Prompt templates
- Workflow standards
- Review checkpoints
- Usage documentation
06Plan
AI and SaaS Product Planning
Turn an early product idea into a structured plan that developers and AI assistants can implement responsibly.
- Product charter
- MVP scope
- Requirements
- Acceptance criteria
Selected work
Products and platforms moving from concept toward implementation.
Each project is presented with a transparent status, current milestone, defined problem, solution direction, and documented role.
01Active Development
AI and Workflow Automation
AI Front Desk Platform
The problem
Service businesses may miss inquiries and manage leads, bookings, and follow-up through disconnected manual processes.
The solution
A multi-tenant platform coordinating customer intake, leads, bookings, chat, notifications, and business operations.
Mohamed Sheriff's role
Founder, product owner, solution architect, requirements author, and AI-assisted developer.
Technologies and methods
- Next.js
- TypeScript
- Supabase
- PostgreSQL
- n8n
Current milestone
Tenant-aware public intake, booking, lead, and chat runtime implemented and verified.
02Foundation and Product Planning
Community Technology Platform
Global Diaspora Nexus
The problem
Diaspora organizations, communities, services, and opportunities remain fragmented across regions and platforms.
The solution
A structured global platform concept connecting diaspora organizations, identity, business, culture, relocation, investment, and community resources.
Mohamed Sheriff's role
Founder, product strategist, research lead, and requirements architect.
Technologies and methods
- Product Architecture
- SaaS Planning
- Data Modeling
- AI-Assisted Research
Current milestone
Product foundation, MVP scope, agent rules, backlog, and initial platform requirements documented.
03Requirements Development
AI Media Operations
Automated AI Media Factory
The problem
AI-assisted media production often depends on disconnected tools, inconsistent workflows, and limited governance.
The solution
A multi-tenant platform concept for coordinating research, prompts, agents, assets, workflows, production, publishing, and analytics.
Mohamed Sheriff's role
Founder, product owner, systems planner, and requirements author.
Technologies and methods
- Multi-Tenant SaaS
- AI Agents
- Workflow Automation
- Media Pipelines
Current milestone
Vision, architecture, roadmap, business requirements, personas, authentication, authorization, and tenant requirements under development.
Why work with Mohamed
Business understanding and technical structure in one conversation.
Effective AI and automation work requires more than selecting software. It requires clear priorities, reliable information, stakeholder understanding, documented decisions, and practical execution.
Learn more about Mohamed- 01
Technical and executive perspective
Experience across software, databases, data, telecommunications, consulting, operations, and organizational leadership supports both technical and business conversations.
- 02
Problem-first solution design
The process starts by understanding the current workflow, constraints, stakeholders, and desired outcome before selecting technology.
- 03
Documentation that supports execution
Product charters, requirements, workflows, architecture decisions, acceptance criteria, testing plans, and roadmaps create continuity and reduce ambiguity.
- 04
Responsible implementation
Data quality, security, privacy, human review, governance, adoption, and operational ownership are considered alongside technical capability.
Selected experience
Experience connecting technology, operations, data, and leadership.
A professional journey spanning technical implementation, consulting, telecommunications, executive responsibility, data, and technology entrepreneurship.
2023 — Present
Position 01
Founder and Solutions Builder
Anunnaki Technology Solutions LLC
Developing AI, automation, SaaS, media, education, and community-platform initiatives through structured product planning and AI-assisted implementation.
Consulting Experience
Position 02
Senior Database Developer Consultant
Accenture
Supported database, data-quality, validation, reporting, and technology-consulting work within structured client environments.
Executive Leadership
Position 03
Chief Executive Officer and Managing Director
SALCAB
Led organizational operations, strategy, stakeholders, risk, infrastructure priorities, and institutional coordination.
Technology Leadership
Position 04
Information Technology Manager
SierraTel
Managed technology operations and supported telecommunications systems, infrastructure, services, and organizational technology needs.
Consulting process
A structured path from discovery to adoption.
The process keeps business needs, technical decisions, risks, responsibilities, and expected outputs visible throughout the engagement.
Not every engagement requires all seven stages. The process is scaled to the problem, budget, risk, organizational readiness, and desired outcome.
- 01
Discovery
Clarify the problem, stakeholders, desired outcomes, constraints, current systems, and available evidence.
Output: Shared problem definition
- 02
Workflow Assessment
Document the current process, handoffs, delays, repetitive work, data inputs, and decision points.
Output: Current-state workflow
- 03
Opportunity Prioritization
Compare opportunities by value, feasibility, risk, readiness, cost, and organizational impact.
Output: Prioritized opportunity map
- 04
Solution Design
Define the future workflow, requirements, architecture, integrations, responsibilities, and controls.
Output: Solution blueprint
- 05
Prototype or Implementation
Build the smallest useful version needed to test the workflow and validate assumptions.
Output: Working implementation
- 06
Testing and Refinement
Evaluate functionality, accuracy, usability, accessibility, security, and operational fit.
Output: Verified improvements
- 07
Deployment and Adoption
Support launch, documentation, training, ownership, monitoring, and continued improvement.
Output: Operational handoff
Frequently asked questions
Clear answers before the first conversation.
These answers explain how an engagement may begin, what support can include, and how technical and nontechnical stakeholders can participate.
No. A useful engagement can begin with the business problem, current workflow, desired outcome, and constraints. Part of the work is determining whether AI, traditional automation, process improvement, or another approach is the best fit.
Engagements may include assessment, requirements, workflow design, product planning, prototyping, AI-assisted implementation support, testing, documentation, and adoption guidance. The final scope depends on the project and available resources.
Yes. Technical concepts are translated into clear business language, visual workflows, structured decisions, and practical next steps so that both technical and nontechnical stakeholders can participate.
Yes. Product-planning work may include a product charter, target users, MVP scope, functional requirements, workflows, architecture considerations, roadmap, acceptance criteria, testing plans, and implementation priorities.
These concerns are considered from the beginning. The exact approach depends on the data, users, integrations, industry, and risk level. Where specialist legal, compliance, or cybersecurity advice is required, that need is identified rather than overstated.
The consulting model is designed to support remote discovery, assessment, planning, documentation, review, and implementation coordination. Specific engagement arrangements are confirmed during the initial discussion.
Begin with the problem
Not sure whether your AI or automation idea is ready?
Start with a focused conversation about your goals, current workflow, constraints, and the outcome you are trying to achieve. You do not need to arrive with a finished solution.