Organizations
AI Consulting &
Integration
Adopt AI deliberately, responsibly, and where it genuinely helps.
Most organizations feel pressure to adopt AI, and many respond in one of two ways: they stall, unsure where to begin, or they rush into tools they don't fully understand. We take a different approach. Our consulting is vendor-agnostic and starts with your actual business problems, then works backward to the tools that solve them.
You won't get buzzword-heavy slide decks or existing software rebranded as "AI-powered." You'll get practical integration where AI adds real value, and a straight answer where it doesn't.
"Too many AI decisions are driven by vendor demos and the fear of falling behind. Very few are driven by evidence."
The Challenge
AI is advancing faster than most procurement processes, due-diligence practices, and in-house expertise can follow. Vendors make bold promises, while the real risks get too little attention: sensitive data sent to third-party models, vendor lock-in, confident errors in high-stakes decisions, and pricing that is hard to predict.
The organizations that struggle most aren't the ones moving slowly. They're the ones moving without a plan: deploying tools with no governance, connecting AI to systems without knowing what data it can reach, or investing in capabilities that never tie back to business outcomes. Getting it right takes an advisor who isn't selling you a platform.
Services
How We Help
Six practice areas that cover AI adoption from first assessment to long-term governance.
AI Strategy & Readiness Assessment
Where can AI genuinely help your organization? We review your workflows, data, and team capabilities to find opportunities with high impact and low risk. You get a prioritized roadmap, not a 200-page report.
Workflow Automation & Agentic AI
We automate repetitive work such as document processing, email triage, data entry, reporting, and routing customer inquiries, using AI connected to the systems you already run. For more complex operations, we build algorithmic agents that carry multi-step tasks from trigger to completion.
Custom AI Tools & Chatbots
AI assistants built on your own documentation, policies, and knowledge base: internal help desks, customer support assistants, and research tools, powered by your data and deployed on your infrastructure.
Data Analysis & Insights
Turn your data into decisions with AI-assisted dashboards, plain-language questions against your databases, trend forecasting, and anomaly detection.
Team Training & Enablement
Practical training that helps your team use AI well: writing effective prompts, verifying outputs, handling data responsibly, and thinking through the ethical questions. The goal is a team of confident, critical AI users rather than passive consumers.
AI Governance & Privacy
Clear policies for how your organization uses AI, covering data handling, vendor evaluation, output review, and compliance. Especially important in regulated industries.
Agentic AI
Algorithmic Agents
Once AI moves beyond answering questions and starts acting on your behalf (running workflows, working inside your systems, and making decisions within set limits), the architecture has to be right from the start.
An algorithmic agent is AI tasked with doing something: routing an incoming request, processing a document, flagging an anomaly, drafting a response for human review, or carrying a multi-step task through to completion without a human driving every step. That is a powerful operational capability, and it is also where poorly built AI creates real risk.
We design and deploy algorithmic agents around your workflows, your risk tolerance, and your compliance requirements. Safeguards aren't added at the end; everything else is built on top of them.
Right Model, Right Task
Not every workflow needs a frontier model. We match capability to complexity, choosing smaller, faster, more auditable models where they fit and local or private processing when the data calls for it.
Sandboxed Access
Agents get only the permissions their task requires. An invoicing agent can read and file documents, but it cannot reach your accounting system or HR records. Every permission is scoped, logged, and revocable.
Human Checkpoints
Multi-step workflows include defined review points, and high-consequence decisions go to a person before they are carried out. Nothing irreversible happens out of sight, because the workflow is designed to prevent it.
Multi-Layer Safety Filters
Every input and output passes through validation that checks for data leakage, out-of-scope actions, hallucinated instructions, and policy violations before anything enters or leaves the system.
Audit Trails & Rollback
Every agent action is logged, and every meaningful change can be reversed. You can always see what an agent did, when, and why, and you can undo it.
Built Bespoke, Not Bolted On
We don't bolt an AI API onto off-the-shelf automation and call it finished. Each agent is built for your specific workflows, with governance designed in from the first conversation.
How We Work
Our Process
Four stages, from the first conversation to lasting capability inside your team.
Assess & Discover
Before recommending anything, we review your workflows, data, existing tools, and risk tolerance. What are you actually trying to solve? Where is AI likely to help, and where would it create new problems? You come away with clarity, not a sales pitch.
Prioritize & Plan
We rank opportunities by value, risk, and effort, then turn them into a practical roadmap. Early wins come first to build confidence and justify the next phase, and you never commit to a vendor before you understand the trade-offs.
Implement & Govern
We deploy in stages, with human oversight built in from the start. Data handling policies, output review, vendor access controls, and rollback plans keep adoption deliberate rather than reckless.
Train & Evolve
Our goal is your team's capability, not dependence on us. Hands-on training, clear documentation, and quarterly reviews keep you current as the technology changes, instead of scrambling to catch up every six months.
Organizations We Work With
Who We Serve
From lean nonprofits to growing businesses, we meet organizations where they are.
Small Businesses & Sole Proprietors
For solo operators and small teams, AI can take on admin, communications, and repetitive tasks, leaving more time for the work only you can do.
Nonprofits & Associations
Lean teams with big missions can use AI for grant research, donor communications, reporting, and administrative work, leaving more capacity for the mission itself.
Professional Services
For practitioners and service firms, AI can handle scheduling, documentation, research, and routine correspondence, so your expertise stays focused on the people you serve.
Founders & Growing Teams
Getting AI right early gives a growing team a lasting advantage. Good tools, habits, and governance compound as the business scales.
Our AI Philosophy
At Distributed Technologies, we think of AI as algorithmic intelligence: sophisticated systems that recognize patterns, reason through problems, and surface insights at machine speed. The framing is deliberate. It treats AI as a powerful computational tool that works alongside human judgment, not as something autonomous or self-directed. The organizations that benefit most from AI keep that distinction clear. They know what AI can do, what it can't, and what it should never decide on its own. When we deploy algorithmic agents (AI tasked with acting, not just answering), that philosophy becomes engineering: sandboxed permissions, defined human checkpoints, and layered controls built in from the start.
- ✓ Humans stay in the loop. AI informs decisions; it doesn't make them on its own
- ✓ Your data stays yours. We evaluate every tool on how it handles data, not just on features
- ✓ We'll recommend against AI when it isn't the right fit. An honest answer is always the right one
Further Reading
How We Think About AI in Practice
Field notes from our model testing, vendor reviews, and safeguard work.
How to Actually Evaluate an AI Model: Rubric-Based Testing for Real-World Work
Public leaderboards won't tell you which AI model fits your work. Here's how we build test sets, write rubrics, and score blind in our benchmarking lab, plus a version a small team can run in an afternoon.
Read articleBefore You Hand Over Your Data: A Due-Diligence Checklist for AI Vendors
How we vet AI tools before recommending them: provenance, data handling, security, red flags, contracts, and getting your data back out.
Read articleConnecting AI Assistants to Your Business Tools Safely: MCP, Agents, and Least Privilege
Hooking an AI assistant up to your email, files, and CRM can save real time. Here's how to threat model it and the controls we put in place before granting an agent access to anything that matters.
Read articleWhy AI Guardrails Block the Wrong Things: False Positives, False Negatives, and Getting Safeguards Right
Content filters and safety classifiers fail in two directions: blocking harmless requests and letting harmful ones through. Here's how organizations deploying AI assistants can test, tune, and layer safeguards that actually fit their users.
Read articleRunning Private AI Models for Your Organization: A Practical Guide
When self-hosting open-weight AI models makes sense for a small organization, how Ollama and vLLM differ, and how to secure and evaluate what you run.
Read articleAI-Forged Documents: How to Verify Who You're Really Dealing With
Forged invoices, bank letters, IDs, and fake company sites are now cheap to make. A practical, risk-based verification playbook for small organizations.
Read articleStart the Conversation
Tell us about your organization and what you hope AI can do for it.