You don't need
more software.
You need leverage.
The Geekio Project designs, builds, and ships AI solutions across the stack: autonomous agents, intelligent automation, custom applications, and the cloud platforms underneath. Grounded in real production systems, governed and handed over for your team to run.
One method.
Four fronts.
We build AI solutions across the stack and ship them to production: autonomous agents, intelligent automation, applications, and cloud. Four fronts, one method behind all of them.
AI Systems & Agents
Systems that reason, retrieve, and act.
Autonomous agents and LLM-backed systems that do real work: reading, deciding, calling tools, and answering from your own knowledge. Built with approval gates on anything that sends, spends, publishes, or deletes.
- Autonomous agents with real tool access
- Retrieval-augmented answers from your own documents
- Approval gates on every irreversible action
- Model-agnostic: Claude, Azure OpenAI, or both
Custom Applications & SaaS
Products your customers log into.
Web and mobile applications built to ship and to scale: multi-tenant from day one, with authentication, subscription billing, and the data isolation a real product needs.
- Web and mobile from a shared codebase
- Multi-tenant architecture with data isolation
- Subscription billing wired in from the first release
- Role-based access and secure authentication
Intelligent Automation
Rules where rules win. AI where judgment is needed.
We automate the manual work end to end, using deterministic rules where they are more reliable and AI only where it genuinely adds judgment, then instrument the whole thing so you can see what it does.
- Process mapping that finds the bottlenecks you've normalized
- RPA and API automation across your existing stack
- Exception handling, retries, and alert routing
- Dashboards showing exactly what ran and what it saved
Cloud, Data & Private AI
The foundation everything else runs on.
Cloud infrastructure as code, data pipelines, and modernization on Azure and AWS. For regulated teams whose data cannot leave, we add self-hosted inference that keeps documents inside your environment.
- Infrastructure as code on Azure and AWS
- ETL and real-time data pipelines
- Self-hosted inference when data cannot leave
- Zero hardcoded credentials, managed identity throughout
Not sure which front your problem sits on?
Take the B.O.M.A. DiagnosticWe govern intelligence.
Others just consume it.
Most AI work fails not because the model is weak, but because nobody decided what it was allowed to do. Four commitments, in every system we ship.
Governed by Default
Every system we build runs on B.O.M.A.: boundaries set before objectives, objectives before tooling. Governance isn't a review step at the end. It's the architecture.
Human in the Loop
Agents operate independently, but ask before they send, spend, publish, or delete. Autonomy where it compounds. Approval where it counts.
Model-Agnostic by Design
Claude for reasoning. Azure OpenAI for infrastructure. The right model for the task, swappable without a rewrite, because today's best model isn't next year's.
Azure-Native Security
Managed Identity and Key Vault. No hardcoded credentials, no keys in environment files, no exceptions. Built to survive the security review, not just the demo.
Built to be handed over.
Continuity is engineered into the deliverable. It does not depend on any one person staying available. Every engagement ends with a system your team can operate.
An operator runbook with every build
Every engagement ships with an operator runbook, architecture documentation, and a handoff session. Your team can run the system without us.
Graceful degradation by design
When an external dependency fails, the system keeps working on a reduced path rather than stopping.
Feature-flagged rollout
Changes ship behind feature flags, so new behavior can be turned on and off without a deploy.
Incident response before go-live
We document incident response and escalation paths before launch, not after the first incident.
Fixed scope, fixed price
No hourly billing and no open-ended engagements. You know the number before we start.
The B.O.M.A. Method
Governing intelligence
instead of just consuming it.
B.O.M.A. is the framework behind every engagement, a structured method for working with AI that produces progress, not just novelty. Without structure, even the best AI produces impressive demos that don't ship.
Break the Ice
Every engagement opens with a real conversation, not a form, not a brief. We learn how your team actually works, where the friction lives day-to-day, and what a genuine win looks like for your business. This isn't small talk. It's the foundation that governs everything that follows.
Outline the Goal
We force precision on the end state before a single tool is chosen or line of code is written. What does the automated version produce? What does it look like when it's working? Vague goals produce clever demos. Precise goals produce deployed systems that actually change your numbers.
Map the Boundaries
We document everything that governs what we can build: your current stack, your team's capacity, your data access, compliance requirements, and what can't change. Boundaries shrink the solution space and eliminate options that wouldn't survive contact with reality. This is where bad ideas get killed cheaply.
Assign + Iterate
With the goal clear and the boundaries mapped, we give AI specific, bounded jobs, and keep humans in the loop for decisions that require judgment. Then we iterate: real data, real feedback, real refinement. The output of each cycle informs the next. Systems built this way don't just work at launch. They get better over time.
The Assign + Iterate phase feeds back into the next cycle, every loop makes the system more precise.
Ready when you are
The right automation
pays for itself in weeks.
One 30-minute call is enough to know whether we can help, and which workflow we'd automate first. No commitment, no pressure.
What we've built.
Real systems we have built, described without client names and without invented numbers. This is the shape of the work.
Document intake and extraction pipeline
A daily unattended pipeline for a regulated procurement environment. It pulls documents from external portals, extracts structured fields from unstructured PDFs, and writes validated records into a downstream system of record. Inference runs self-hosted, so documents never leave the client environment, and the pipeline keeps running when the model is unavailable, falling back to deterministic parsing. It is one piece of a larger platform we took from concept to production in months, with idempotent processing, transactional integrity, full audit trails, and a documented recovery plan.
Multi-tenant platform with data isolation
A platform that serves many tenants from a single deployment, with isolation enforced at the database layer rather than in application code. Each tenant's records are separated by row-level security, and identity and single sign-on are handled by a dedicated service.
Mobile product with subscription billing
A React Native mobile product with subscription billing, built on a database schema that evolved through more than two dozen migrations rather than a single-shot build. Access is scoped per user with row-level security, and releases ship behind a documented update process.
Security hardening and PII protection
A security review across application and infrastructure for a client with strict data-handling requirements: what the system can reach, under whose credentials, and what is logged. The work covered PII protection controls, credential handling, and hardening ahead of production.
What we can build for you.
Common problems we solve, and the shape of the system we build for each. If one of these fits your situation, the discovery call is where we scope it to your numbers.
Automated executive reporting
Teams often assemble daily or weekly reports by hand: pulling from billing, a CRM, and a database, then formatting and sending them. We build a pipeline that gathers the data on a schedule, writes a plain-language summary, and posts it where your team already works. The manual assembly stops.
Tier-1 support automation
For teams handling a high volume of repetitive requests, such as order status, returns, and shipping questions, we build a system that classifies each request, retrieves the relevant order and policy context, and either resolves it or routes it to a person with the full context already loaded. Routine questions are handled automatically, and anything needing judgment goes to a human.
Multi-tenant SaaS for regulated domains
When a product serves many customers from a single deployment, especially in a regulated space, the foundation has to be right early. We build multi-tenant platforms with data isolation at the database layer, audit logging, role-based access, and subscription billing wired in from the first release. The architecture scales as you add customers, without a rewrite later.
See your situation here, or something close to it?
Book a Discovery CallThree ways to start.
Priced to the problem, not by the hour.
The headline price on each entry point is the floor. Where an engagement lands inside its range is set on a discovery call, against the cost of the problem and the constraints around it. Fixed scope and fixed price once we agree on it. No hourly billing.
Assessments
Start with a clear read on where AI pays for itself.
Fixed scope, fast, and designed to stand alone. Many clients start here and stop, which is fine.
- AI Leverage Diagnostic$4,500
One week. Ranked opportunities, build vs buy, 90-day roadmap.
- Isolation & Agent Security Audit$12,500 to $30,000
Two weeks. What your AI can reach, under whose credentials, and what is logged. Tenant isolation and data-boundary review. Annual repeat.
- Architecture Review$6,500 to $15,000
An existing system reviewed for reliability, isolation, and scale, with prioritized findings.
AI Systems
Free discovery call included.
- Production Sprint$18,000 to $35,000
One workflow automated end to end, live in your environment in two weeks.
- Private AI Deployment$45,000 to $120,000
Self-hosted inference inside your boundary. Your documents never leave.
- Multi-Tenant Platform Build$85,000 to $250,000+
Isolation enforced at the data layer, identity, billing, connectors.
- Custom AI Application$25,000 to $150,000+
Product build, web and mobile, with subscription billing.
Every engagement: runbook, handoff, and 30 to 60 days of post-launch support.
Schedule Discovery CallOperator Retainer
Ongoing capacity. Systems drift; we keep yours honest.
- Continuous monitoring, alerting, and incident response
- Cost tuning and model updates
- Architecture reviews
- Team training on operating AI systems
- AI governance frameworks
- Priority access
The Discovery Call
A 45-minute call. We map the workflow, identify the constraint, and tell you what it would take to fix. If the work is not a fit, we say so. No preparation required and no obligation.
B.O.M.A. Diagnostic
4 questions.
Your first B.O.M.A. session.
This is the B.O.M.A. framework in miniature. We Break the Ice, Outline your goal, and Map your constraints. Then we Assign you a specific starting point. Free. No sales call required.
B.O.M.A. Diagnostic
Four questions that walk you through Break the Ice, Outline the Goal, and Map the Boundaries, then we Assign you a concrete next step. Takes 60 seconds.
Let's talk about
your systems.
Fill in the form and we'll respond within one business day with a specific recommendation, not a generic sales pitch.
Response in < 24h
A real person reviews every submission.
No-pressure discovery call
30 minutes. We assess fit honestly. If we're not the right match, we'll say so.
Specific proposal
Scoped to your actual problem, not a menu of services.
How we work