Complex business problem. Clear AI solution.
Best for: businesses whose requirement spans multiple systems, vendors, or AI technologies — and where the right technology isn't known yet.
The business problem
When your business needs more than an off-the-shelf AI tool, the hard questions arrive before any build: what should be built, what should be bought, how the pieces should work together, and how to get the result into production without it becoming a second job for your team.
If nothing changes
Tools get bought one at a time, each solving a fragment, and the integration work nobody scoped becomes the project — or the requirement stays unmet while the market moves on.
Your AI Solutions Architect
Start with the outcome, not a predetermined technology.
TechFortress bridges the gap between a business requirement and a rapidly changing AI technology landscape. The engagement begins with the outcome you need, then works through the process, the systems already in place, the constraints, the economics, and what success has to look like.
From there it determines whether the best approach is an established platform, custom development, system integration, or a hybrid — and TechFortress can remain involved through implementation, testing, launch, and initial optimization.
Vendor-agnostic
The right solution, not a preferred vendor.
TechFortress is not tied to a single AI platform. Technologies are evaluated against your business requirements, existing systems, economics, security, scalability, and expected outcome.
If an established platform solves the problem effectively, it's used. If customization creates an advantage, it's architected. If multiple technologies must operate as one system, the design covers exactly how they work together.
The objective is not to sell another AI tool. It is to build the right system for the business.
What you receive
AI Solutions Architecture
- Business and workflow discovery
- AI opportunity and feasibility assessment
- Technology and vendor evaluation
- Build vs. buy vs. hybrid analysis
- Solution and integration architecture
- API and data-flow strategy
- Security and scalability considerations
- Implementation roadmap and vendor coordination
- Technical direction for your internal team
- Testing and acceptance criteria
- Production-readiness review and go-live oversight
- Initial performance optimization
Process
- 1. Discover — the business outcome, process, systems, constraints, and success criteria
- 2. Evaluate — platforms, vendors, integrations, economics, and technical options
- 3. Architect — components, integrations, data flows, responsibilities, risks, and the plan
- 4. Execute — direct internal resources, vendors, and technical partners through implementation
- 5. Validate — real workflows, integrations, exceptions, escalation paths, security, reliability
- 6. Optimize — measure the first results and identify the next improvements
Deliverables
- Written solution architecture and integration design
- Build / buy / hybrid recommendation with reasoning
- Phased implementation roadmap
- Acceptance criteria and production-readiness review
Where it applies
Appropriate use cases
- Customer operations
- AI voice, customer service, scheduling, transactions, payments, lead qualification, and intelligent escalation.
- Sales operations
- Lead capture, qualification, routing, CRM integration, and automated follow-up.
- Business operations
- Workflow automation, approvals, document processing, reporting, and cross-system integration.
- Back-office operations
- Accounting workflows, administrative processes, reconciliation, data movement, and operational automation.
- Custom AI systems
- Solutions that combine commercial AI products, existing business applications, APIs, and custom automation.
Common questions at this stage
- How do I know AI is even the right answer here?
- That's what the Opportunity Brief is for. It can and does recommend a non-AI approach, or further discovery, when that's the honest read. TechFortress does not recommend AI where another approach fits better.
- What if the initial direction turns out to be wrong?
- Direction, scope, assumptions, exclusions, and success criteria are written down and approved before production starts, which is where a wrong direction is cheap to catch. After that, changes run through change control against that same written scope — so a change is a visible decision with a stated cost, not a quiet re-interpretation.
- Who is actually accountable for the work?
- Steve Dumont, the founder — for strategic oversight and for final quality control on every deliverable. AI increases execution leverage; it does not move accountability anywhere else.
Before it reaches you
Steve Dumont reviews every design decision personally before it goes to your team or your vendors, and leads the engagement end to end.
Investment
Timeline and starting price
Typical timeline: 2–6 weeks to an approved architecture; implementation scoped from there
Starting investment: from $7,500
Founding Client rate: $5,000
Third-party software, licensing, usage fees, and substantial custom development are separate unless specifically included in the project scope. No hourly rates are published; every engagement is a defined scope.
What affects the final price is scope — how much is being built, what it has to integrate with, and how much of the input already exists. Scope is defined and approved before execution.
Fit
TechFortress is probably not the right fit if your primary requirement is the lowest-cost website, template-quality slides, a basic chatbot, or commodity AI output.
Start here
Get an Opportunity Brief for ai solutions architecture
Questions