AI development company for Cambridge MA biotech, computational biology, and MIT-adjacent research startups.

We do not operate a Cambridge or Boston office. Aiinfox runs from our Mohali, India HQ and a Frisco, TX office. For Cambridge clients that need Eastern business-hours coverage, our Frisco pod runs a US-Hours rotation on a late-CT shift that covers ET 11am-to-8pm with senior engineers live on Zoom, and the Mohali team picks up Cambridge afternoons via an early-IST start. For on-site engagements at Kendall Square, the Broad, the Wyss, the MIT campus, or partner-hospital sites (kickoff, milestone reviews, security walk-throughs), we travel to Cambridge on a scheduled cadence rather than maintaining a sub-scale local team at Boston-area rates.

The same engineers, but a different engagement shape. Boston engagements lean into enterprise-healthcare with Mass General Brigham-adjacent operators, Back Bay financial services, and Financial District asset managers — multi-quarter, multi-stakeholder, with a formal security review. Cambridge engagements tend to be tighter and faster: pre-Series-B biotech spinouts, MIT and Broad-adjacent computational-biology teams, and research-SaaS scaleups where the science is the moat. We bring the same eval-first discipline, but the scope is usually a single high-leverage system (RAG over internal scientific corpora, a regulatory document-intelligence pipeline, a wet-lab copilot) rather than a multi-system enterprise rollout. Pricing reflects that — Cambridge pilots typically land in the $25,000 to $60,000 range with v1 production builds at $60,000 to $120,000.

Carefully and in writing before any code is written. Academic spinouts in Cambridge typically have one or more of: an exclusive licence from an institutional tech-transfer office (MIT TLO, Harvard OTD, the Broad's institutional agreements); a sponsored-research agreement that constrains what data can leave the institution's network; or a consortium data-use agreement (with GTEx, TCGA, the Broad's DUOS, or a hospital data partner). We read the relevant clauses in the kickoff scoping pass, structure the engagement so IP we create is assigned to your entity (your code, your IP), and explicitly scope which institutional data classes can and cannot reach a managed inference endpoint. Where consortium DPAs forbid egress, self-hosted Llama 3 on vLLM inside your VPC is the default.

Yes. Our healthcare engagement defaults are HIPAA-aligned. BAAs are signed before any PHI is shared. Deployments default to US-East-1 (N. Virginia) or US-East-2 (Ohio) inside customer-controlled AWS, Azure, or GCP accounts so PHI never leaves a HIPAA-eligible region. Every model and tool call is audit-logged with input, output, prompt version, and operator identity — so the privacy officer accountable under HIPAA has the evidence required for an OCR examination. For Cambridge digital-health spinouts with MGB, Beth Israel Deaconess, or Boston Children's-adjacent integration paths, we map controls into the partner-hospital BAA template and align audit-log retention with the partner's existing HIPAA security risk assessment.

Yes. Any system processing personal information of Massachusetts residents — which covers most Cambridge MA SaaS, digital-health, and edtech operators — is in scope for 201 CMR 17.00, the Standards for the Protection of Personal Information of Residents of the Commonwealth. The written information security program (WISP) requirement is satisfied by the engagement DPA plus security exhibit; encryption-at-rest and in-transit is the default; data-access controls map onto our standard SOC 2-aligned deployment pattern. For Cambridge operators with California, New York, or multi-state US customers, we layer CCPA + CPRA, NY SHIELD, and the Colorado / Virginia / Connecticut state privacy obligations onto the MA 201 CMR 17 baseline.

Yes — that engagement pattern is one of the things we run most often for Cambridge digital-health spinouts. We deploy our agent or pipeline inside your AWS, Azure, or GCP account and consume the partner-hospital data via the connectivity path your partner has already approved (typically a site-to-site VPN, a private endpoint, or a vetted FHIR API). We do not ask partner hospitals to relax their security posture for our engineers. Where the partner requires named-engineer attestations, we provide them; where the partner requires the inference to run inside their VPC, we self-host Llama 3 on vLLM there. The senior engineer on your kickoff is the senior engineer who attests against the partner-hospital security review.

Your call. We default to AWS US-East-1 (N. Virginia) or US-East-2 (Ohio) for Cambridge clients — lowest-latency east-coast regions with full HIPAA-eligible service coverage. We will run inside your AWS, Azure, or GCP account in any US region you specify. For inference, Claude (Anthropic) and GPT-4o (Azure OpenAI) have US-East endpoints we route to explicitly; for Kendall Square biotech operators whose consortium DPAs forbid egress to managed inference APIs, we self-host Llama 3 on vLLM inside your VPC with zero data egress to non-customer endpoints. Your DPA spells out the exact data path.

Most pilots at Aiinfox land between $15,000 and $35,000 fixed-price for a focused proof-of-value with acceptance criteria written into scope. V1 production builds land between $60,000 and $120,000 — an AI agent, a RAG system, a document-intelligence pipeline, or a bespoke ML model with evals and guardrails. Larger multi-quarter engagements with fine-tuning, custom evals, and HIPAA-aligned clinical workflows typically reach $180,000 to $320,000. Cambridge pre-Series-B spinouts get the same senior engineer the enterprise client gets — the rate difference is in scope, not in the seniority of the people in your standup.