AI Engineering Studio
Most AI firms pitch decks.We ship products.
neosphere is a boutique AI engineering firm. We partner with mid-market and enterprise companies to design, build, and deploy AI.
Book a callAI that works in the real world,
not the demo.
The gap between an AI demo and a system your team actually depends on is enormous. Most firms bridge it with promises. We bridge it with deep engineering and product experience, the kind built over years at companies and institutions that don't tolerate failure.
We're a small team by design. Every engagement gets senior attention, fast iteration, and honest feedback. We'll tell you when AI is the right solution, and when it isn't.
What we build
AI Integration
Connect AI to your existing data, tools, and workflows. We build the layer that makes your systems intelligent, without forcing you to replace what works.
RAG · Agents · APIs
End-to-End AI Products
From strategy through deployed product. We own the full build: product design, engineering, and delivery, so you're not coordinating five vendors.
Product · Engineering · Delivery
AI POC in 4–6 Weeks
Not sure what's possible? We run a scoped proof of concept on your real data and deliver a working prototype in 4–6 weeks. See results before committing to a full build.
Low-risk · Fast · Validated
How we work
- 01
Discovery call
30 minutes. We map your use case, your data, and what success actually looks like for your team.
- 02
Scoped proposal
A clear plan with milestones, timeline, and fixed pricing. No ongoing seat licenses or SaaS lock-in.
- 03
Build & iterate
We ship fast and show you working software early. You stay in the loop, not waiting on quarterly updates.
- 04
You own it
Everything we build is yours. Source code, infrastructure, documentation. No dependency on us to keep it running.
The team
Built by engineers who've done it before. We've shipped AI from inside enterprise institutions and built products from zero to production across multiple industries. We bring the rigor of those institutions and the velocity of early-stage startups, because we've lived in both.
Microsoft
Siemens
UNDP
Yale
Point72
Case studies
We replaced manual document review with agents that classify, route, and approve autonomously.
Enterprise · Document IntelligenceProblem
Every PDF needed multiple humans to read, classify, and approve. No enforcement of compliance rules. The more documents came in, the slower everything got.
What we built
An agentic document intelligence platform. Agents extract clauses and compliance signals from PDFs, policies, and contracts. Multi-agent orchestration handles classification, review, and approval with role-based access and a control tower for audit visibility.
Outcome
Documents that sat in review queues for days now flow through governed workflows autonomously. Built-in compliance tracking and a system that improves through feedback loops.
Agentic AI · React · AWS (S3, DynamoDB, Cognito) · Multi-Agent Orchestration
We built a product that lets anyone talk to their data without knowing SQL.
Internal · Data TeamsProblem
Data teams spend most of their time answering the same questions: a chart here, a number there. Every request goes into a backlog. Business teams wait days for answers they needed the same morning.
What we built
A standalone analytics workspace. Connect your data, ask questions in plain English, get charts and dashboards back instantly. Dashboards can be saved and shared across the team.
Outcome
Business teams stopped waiting. Data teams stopped fielding repetitive requests. Questions that used to sit in a queue for two days now get answered in seconds.
Agentic AI · Claude · GPT Agents · Python · Postgres · Next.js
You know AI should be doing more for your business.
30 minutes with us and you'll know exactly what to build, what it costs, and whether we're the right team to build it.