AI Consulting in Boston

Yes, and that's usually the right architecture. Most regulatory document automation doesn't require the system to understand the underlying science — it needs to understand the submission structure, the agency's formatting expectations, and where the current data drops into prior module language. We scope builds with read-only access to the specific document repositories the RA team actually uses, typically SharePoint, Veeva Vault, or a shared drive structure, and we keep compound data, trial results, and IP-sensitive material outside the model's context entirely unless the client explicitly scopes it in. The assistant handles the structural and administrative layer — pulling prior language, flagging gaps, formatting for submission — while the RA team handles scientific accuracy. That separation isn't just a data hygiene preference; it's the right division of labor.

Every healthcare build runs on BAA-covered infrastructure from the ground up. That means a signed Business Associate Agreement with every vendor in the data path — the model endpoint provider, the hosting layer, any middleware touching PHI. We use enterprise API endpoints from Anthropic or Azure OpenAI where zero-retention terms are contractually enforceable, not a checkbox in a terms of service. Access controls are scoped to role and department: a prior-auth automation tool for the billing team doesn't have access to clinical notes, and a clinical documentation assistant for a specific department is walled from unrelated patient records. We map the full data flow on paper before any integration begins, and the compliance review package we deliver at go-live is written for the health system's privacy officer and legal team, not just the IT department. HIPAA isn't a feature we add at the end — it's the constraint the architecture is built around from the start.

The core function is compression: taking the repetitive administrative work out of each new application cycle so the grants coordinator and PI can focus on the science and strategy. In practice that means the assistant maintains a library of the lab's or center's prior successful submissions, knows each funding agency's specific formatting requirements and common reviewer concerns, and can draft boilerplate sections — facilities and resources, data management plans, human subjects narratives, budget justifications — to a 70% finish based on the application type and the PI's prior work. The coordinator reviews and refines rather than authors from scratch. For post-award compliance, the same system can track reporting deadlines, pull the relevant progress data from the lab's project management tools, and draft progress reports against prior deliverables. The build doesn't replace the grants professional's judgment — it removes the parts of the job that shouldn't require judgment at all.

Several. Firms under SEC, FINRA, or state Division of Securities oversight have books-and-records requirements that apply to any system involved in investment advice, client communications, or trading-related decisions — meaning the AI tooling and its outputs may need to be logged, retained, and producible on exam. We build with that requirement in mind: structured audit logs, output retention tied to the firm's existing compliance calendar, and documentation that the CCO can hand to an examiner. For firms running internal risk or credit models, there are additional model-governance considerations around validation, bias testing, and change control. We're not a compliance consulting firm and we don't provide regulatory legal advice, but the builds we deliver for regulated financial firms include the compliance documentation and infrastructure the firm needs to put the tool in front of their CCO without surprises.

Most focused builds — one capability, scoped tightly — run two to four weeks from signed agreement to go-live. The process starts with the $99 AI readiness audit, which maps the actual workflow, surfaces where the time is going, and identifies the highest-leverage place to start. That audit report is the blueprint for the build scope; nothing gets estimated before it's done. From there, if the bottleneck is clear, we scope a fixed-price build and begin. If the operator isn't sure which workflow to prioritize, a $497 Founder Review Call — ninety minutes, written prioritization memo afterward — ranks the candidates before any build budget is committed. Golden Horizons works with one build at a time per client during the initial engagement: one capability, done right, with the integration and compliance architecture to match the regulated environment. That focus is what keeps the timeline honest.