Advisory and technical delivery tailored to AI-forward organizations — from strategic roadmaps to production-grade builds. Every engagement is scoped to your stack, your constraints, and the outcomes that actually matter to you.
Most organizations don't have an AI problem — they have an AI readiness problem. We work with your leadership and technical teams to map exactly where AI can deliver real, measurable value in your environment, and just as importantly, where it can't.
We design integration strategies that fit your existing stack, your compliance constraints, and the way your organization actually makes decisions — not the way a vendor demo assumes it does. Governance isn't an afterthought here; it's designed in from day one so your AI program holds up to regulatory scrutiny.
The output is a concrete, prioritized roadmap your team can execute against — one that accounts for risk, build-vs-buy tradeoffs, and the internal change management required to make adoption stick.
Salesforce is one of the most powerful platforms on the market — and one of the most commonly underutilized. Years of customization, org merges, and accumulated technical debt tend to produce a CRM that technically works but actively gets in the way of the people using it.
We audit your org from top to bottom: data model integrity, automation logic, integration health, field usage, user adoption gaps, and governor limit exposure. Nothing gets optimized until we understand exactly why it was built the way it was.
The result is a Salesforce environment that surfaces the right data to the right people at the right time — with automations that reduce workload instead of creating new failure points, and a data model that supports reporting you can actually trust.
Off-the-shelf Salesforce functionality covers 80% of what most organizations need. We build the other 20% — the differentiating layer where your business processes are too specific, too complex, or too critical to fit inside a standard config.
From custom Apex classes and triggers to Lightning Web Components and full-featured internal applications, every build starts with a requirements workshop where we work through your use case in detail — so the first thing we ship is something your team will actually use, not something that needs three rounds of rework.
We build with test coverage, documentation, and a handoff process that leaves your internal team capable of maintaining what we deliver — because a build that creates permanent dependency isn't a win for anyone.
AI systems introduce a new class of security risk that traditional frameworks weren't designed to address. Prompt injection, excessive tool permissions, model inversion attacks, and data leakage through inference are real threats that don't show up on a standard vulnerability scan.
We assess how AI is integrated into your environment — across models, agents, APIs, and data pipelines — and identify the specific attack surfaces your configuration introduces. Our advisory is aligned to NIST AI Risk Management Framework and CIS benchmarks, giving you assessments that hold up to regulatory and audit scrutiny.
If you're deploying Model Context Protocol servers, we review those specifically for permission creep, prompt injection vectors, and tool exposure that extends beyond what your use case requires. Security here isn't a checklist — it's architectural.
The Model Context Protocol is rapidly becoming the standard interface for connecting AI agents to enterprise tools — and with that architectural power comes serious security and governance responsibility that most implementations currently ignore.
We design and deploy MCP servers that give your AI agents scoped, auditable access to the tools they need and nothing beyond that. Whether you're working in Salesforce, internal databases, document stores, or custom APIs, we build the connective layer with permission governance and injection hardening built in from the start.
We also build standalone applications — internal tools, workflow automation, and AI-integrated interfaces — and review existing MCP configurations for organizations that have already deployed but want an independent assessment of what their agents can actually access.