Ship production AI without hiring an in-house AI team. 
Bitontree embeds senior AI engineers into your sprint cadence to build agents, voice AI, RAG, document automation, and workflow systems, for regulated and operations-heavy teams in healthcare, logistics, legal, and SaaS. Then we stay to run, improve, and scale them.
200+
Nightly AI calls supporting complex tasks
Healthcare · Voice AI
90%
Manual work eliminated through AI automation
Logistics · Document AI
60%
Faster sales response across customer interactions
Sales · AI Chatbot
50%
Research time saved with automated insights
Legal · Research AI
Built for the markets where AI has to actually work
We deliver into US healthcare, SaaS, logistics, and legal environments where AI ships under real compliance, real workloads, and real users.
US healthcare-ready
HIPAA-aware delivery with BAA support, audit trails, and PHI-safe pipelines from day one.
SaaS-grade engineering
Production-grade code, observability, and CI/CD, not notebook demos handed over as deliverables.
US-overlap delivery
Daily working-hour overlap with US East and West Coast sprints, standups, and on-call windows.
SOC 2-aware practices
Access controls, secrets management, and vendor posture aligned to enterprise security reviews.
Bitontree has shipped software and engineering for global brands and venture-backed teams, and today builds production AI for healthcare, logistics, legal, and SaaS.
AI solutions we build and run in production
Six capabilities, one team, built into your sprint, shipped into your stack, owned past launch.
AI Chatbot Development
Customer-facing and internal chatbots that handle qualification, support, and self-serve flows on your site, app, or messaging channels. Wired into your CRM, helpdesk, and knowledge base so conversations actually convert and resolve.
AI Agent Development
Goal-driven AI agents that take actions across your tools, booking, routing, drafting, escalating, not just answering questions. Built with guardrails, tool-use logging, and human-in-the-loop checkpoints for work that matters.
AI Workflow Automation
End-to-end automation for the work currently eating your ops team, intake, triage, routing, approvals, and follow-ups. We connect your systems and let AI handle the judgment calls that used to need a human in the loop.
Document AI
Pull structured data out of invoices, contracts, forms, claims, and clinical notes, accurately, at volume, with audit trails. Replaces manual data entry and review cycles with pipelines your finance, ops, and legal teams can trust.
RAG & Knowledge Systems
Retrieval-augmented systems that let your team and customers query your own data, policies, contracts, product docs, support history, with grounded, cited answers. Built on your stack, not a black box.
Live AI systems, named outcomes
Three published production builds running today for healthcare, logistics, and sales teams, with more deployment stories, including Mental Health AI and Legal Research Automation, queued for public case-study publication.
How we build production AI systems
A four-phase path from "we think AI could help here" to "this system is running, monitored, and improving."
01
Discover (Week 1-2)
Structured workshops with your ops, product, and engineering leads to pin down the highest-ROI AI use cases on your actual data and workflows. You leave with a prioritized opportunity map, success metrics, and a build sequence.
Stakeholder workshops
Use-case prioritization
Data and source mapping
Success metrics
Build sequence
02
Design (Week 2-4)
Solution architecture, retrieval design, integration points, eval strategy, and compliance posture. This is where the production plan, not just the demo plan, gets locked.
Solution architecture
Retrieval design
Integration points
Eval strategy
Compliance posture
03
Build (Week 4-16)
Embedded AI engineers build, integrate, and deploy inside your stack with CI/CD, observability, and human-in-the-loop checkpoints from sprint one. You see working software on real data every two weeks, not at the end.
Embedded engineering
Two-week working software
CI/CD pipeline
Observability stack
Human-in-the-loop checkpoints
04
Scale (Ongoing)
After launch we own the running system, monitoring dashboards, eval suites that catch drift, on-call response, prompt and retrieval tuning, and expansion to the next workflow. AI systems decay if no one runs them; we run them with you.
Monitoring dashboards
Drift-detection eval suites
On-call response
Prompt and retrieval tuning
Workflow expansion
How we work with you
Most teams start here
Hire, agency, platform, or embedded team?
There are four ways to get production AI built. Here's why operations- and compliance-heavy teams pick an embedded team.
| Evaluation criteria | In-house AI hire | Generic dev agency | No-code AI platform | Bitontree embedded team |
|---|---|---|---|---|
| Time to first production system | 6-12 months to hire and ramp | Fast to start, slow to production | Quick demos, ceilings on real workflows | Working system in weeks, live in 4-16 |
| Compliance built in (HIPAA, PHI, audit trails) | You build the controls yourself | Usually bolted on after the build | Their compliance posture, not yours | PHI-safe pipelines & BAAs from day one |
| Who runs it after launch | Your team, once you've built one | Hands off at delivery | You operate it | We do, monitoring, evals, iteration |
| Your IP, code & evals | Yours | Varies, often theirs | Locked to the platform | Always yours, code, evals, runbooks |
| Senior AI engineering depth | One or two people, hard to find | Generalists; AI is a side line | No engineering, you're the builder | A senior AI team on your roadmap |
Industries where our AI is already running
Specific systems, specific integrations, specific compliance, not horizontal demos.
Healthcare
We build HIPAA-aware AI for US clinics, digital health companies, and provider groups, clinical documentation, patient outreach, intake, and adherence systems. For scoped healthcare deployments, we support BAAs, PHI-safe pipelines, and integration patterns for Epic, Cerner, Athena, and FHIR-based stacks. Live today: a nightly medication adherence voice system and SOAP-note automation.
Logistics
AI for freight, customs, and supply-chain operators where document load and exception handling slow everything down. We build invoice and document AI, customs paperwork automation, and workflow agents that sit on top of TMS, WMS, and freight platforms. Live today inside a logistics enterprise in Singapore.
Legal
AI for law firms and legal advisory teams, matter intake, legal research, contract review, and case-brief drafting with citations and audit trails. Built for the way attorneys actually work, not generic chat over a document. Deployment running at a US legal advisory firm; public case study pending, with 50% research time saved reported by the client.
SaaS
Embedded AI for B2B SaaS products, in-app copilots, agentic workflows, and RAG over your customers' data with multi-tenant isolation and observability. We build the AI surface area your product team can't get to fast enough, then run it with you.
E-commerce
AI for Shopify, WooCommerce, and Magento merchants, product discovery, support automation, merchandising agents, and post-purchase flows that move conversion and CSAT without breaking your stack.
Manufacturing
AI for plant and operations teams, predictive maintenance, quality vision, and ops copilots wired into ERP, MES, and IoT/sensor data. Built for the realities of OT environments and brownfield systems.
The production stack we ship on
OpenAI, Anthropic, open-source LLMs, vector databases, orchestration frameworks, and the cloud and integration tooling your team already runs, chosen per use case, not per fashion.
AI, Agents & Orchestration
Application & Interface
Backend & APIs
Infrastructure, Cloud & MLOps
Data & Storage
Automation & Analytics
What clients say about working with us
Healthcare, delivery, consulting, and founder teams who shipped with Bitontree.
Healthcare
Bitontree transformed our clinic's workflow with AI SOAP Notes. Documentation that once took hours is now instant, letting providers focus on patient care. Their expertise and commitment to quality truly stand out.
Dr. Josh Franklin
Doctor, Harmony Health Clinic
Enterprise
Yash and his team are great, and I will continue to use them for different enterprise level projects. What drew me was the way they provided suggestions outside of what I asked, which turned out to be exactly what I needed.
Martavis P.
Delivery Manager
Manufacturing
I had the pleasure of working with Bitontree on a cloud-based ERP application, and I was thoroughly impressed with their work. They demonstrated exceptional technical skills, a clear understanding of modern web development, and a proactive approach to problem-solving.
Saurav G.
Consultant
Healthcare
Bitontree transformed our clinic's workflow with AI SOAP Notes. Documentation that once took hours is now instant, letting providers focus on patient care. Their expertise and commitment to quality truly stand out.
Dr. Josh Franklin
Doctor, Harmony Health Clinic
Field Notes From Shipping AI
How we build, evaluate, and run production AI, written by the engineers and leads doing the work.
Let's scope your AI build
Tell us about the workflow, system, or use case you want AI on. We'll come back with an honest read on what's buildable, what isn't, and the shortest path to production, usually within one working day.
6+
Years Of Experience
40+
Skilled Professionals
105+
Projects Delivered
35+
Global Clientele Served
Book a Free AI Fit Assessment
Frequently asked questions
How do you make sure this actually ships to production, not another PoC that dies?
Every engagement is sequenced through our four-phase model, Discover, Design, Build, Scale, and the production plan is agreed before the build starts, not after the demo. We embed AI engineers into your sprint cadence, deploy on real data and real integrations from early sprints, and stay past launch to monitor, evaluate, and improve. The systems on our case-study page are running today, not slideware.
How do you handle security, HIPAA, and SOC 2 requirements?
We default to PHI-safe pipelines, BAA-ready vendor stacks, audit logging, and least-privilege access from day one. For US healthcare clients we sign BAAs and align the architecture to HIPAA before a single line of production code is written. For SaaS and enterprise clients we work to SOC 2-aware practices around access, secrets, and vendor posture so your security review is straightforward.
What's the difference between an Embedded AI Engineering Team and a Project-Based Build?
An Embedded team joins your sprints as ongoing AI capacity, you set the roadmap, we staff the build, and we keep iterating across multiple use cases. A Project-Based Build is a single scoped outcome with fixed deliverables, milestones, and a handover, the right shape when you already know exactly what you want shipped. Many clients start project-based and move to embedded once the roadmap expands.
How long does a typical AI build take?
Discovery and design usually run weeks 1-4. A first production build typically lands between weeks 4 and 16 depending on integration depth, data readiness, and compliance scope. Most clients see a working system on real data within the first month and a production deployment within the first quarter.
What's included in the Free AI Fit Assessment?
A 30-45 minute working session with a senior AI engineer, not a sales rep. You walk through the workflow or system you have in mind, we pressure-test feasibility, flag the integration and data realities, and come back with an honest scope, timeline, and the shortest path to production. If we're not the right fit, we'll tell you.
Which industries do you build for?
Our deepest production experience is in Healthcare, Logistics, Legal, and SaaS, with published case studies and additional deployment stories moving through approval. We also build for E-commerce and Manufacturing teams. If your sector isn't listed but the use case is AI agents, RAG, document AI, or workflow automation, the assessment call is the fastest way to find out if we're a fit.