Boston product companies often marry deep domain expertise with conservative procurement — especially in health, climate, and research tooling where mistakes are costly. Talent drains toward Kendall Square and Cambridge labs; startups in the suburbs scramble for full-stack generalists who can also talk to compliance-minded buyers. MVPs must look credible to enterprise pilots; marketing sites need technical SEO that satisfies diligent reviewers. Local agencies excel at life-sciences branding but may thin out on senior TypeScript capacity. Jythu helps teams ship web apps, patient- or researcher-facing portals (with your compliance lead driving requirements), and LLM assistants that cite sources rather than improvise protocols.
Jythu wires large language models into products you already run — RAG over your docs and databases, tool-calling agents with guardrails, eval harnesses, and cost controls finance can read. Not a chat widget stapled on a homepage. We integrate OpenAI, Anthropic, or open weights behind your VPC with citations, rate limits, and observability baked in. For Boston teams, that usually means fewer contractor handoffs and a partner who will cut scope when the calendar is real.
Greater Boston — biotech-adjacent SaaS, robotics, and academic spinouts on Eastern Time (ET). We tailor AI & LLM integration around local collaboration habits — local proof section, city case study/testimonial, timezone/response-time note.
AI & LLM Integration — nearby services
Built for this market — not a generic offshore brief
Why teams in Boston hire Jythu
Eastern Time overlap plus compliance-aware engineering — we follow your security and privacy checklist, join afternoon calls your researchers can attend, and document data flows plainly.
Senior builders, written scope
Two-week sprints, staging on every PR, and deliverables your team can own — not a black-box ticket queue.
US business-hours overlap
Core standups land in your workday with async PRs ready when you log on.
In-product assistant (NDA)
Support volume and docs sprawl pushed a product team to put answers inside the app. Answers had to cite sources, never hallucinate pricing, and stay under a weekly cost cap.
Result: Hybrid RAG over CMS and product DB with tool calls for account actions behind confirmation. Material share of tier-1 tickets deflected; cost per 1k queries became predictable after caching.
Discover → Design → Build → Launch
Discover
Goals, constraints, and success metrics in a focused discovery pass.
Design
Figma flows approved before TypeScript starts — fewer surprises later.
Build
Two-week sprints with staging deploys you can click every cycle.
Launch
Cutover checklist, monitoring, and a 30-day warranty on fixed projects.
Questions teams ask before kicking off
Do you build health-adjacent products for Boston teams?
We implement to your requirements and compliance guidance — HIPAA or similar frameworks are your legal call; we document data flows and access controls.
How fast can a pod start for a Cambridge-area startup?
Brief, proposal, and trial sprint typically inside two to three weeks — faster when your access and backlog are ready.
Will you join our existing design system?
Yes. We extend Figma tokens and component libraries rather than inventing parallel UI languages.
How do you keep AI answers grounded in our data?
We start with a discovery call, then a written in/out list for AI & LLM integration. Estimates follow constraints — timeline, stack, and who owns the repo — not a one-size quote calculator.
5.0 · Rated by 50+ clients
Ready to start a project?
The first discovery call is on us. Bring constraints — we will bring a timeline and a cut list.