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New MCP server development for Claude

We build AI agents and real-time FinTech products that ship.

Senior engineers who design, build and run production AI agents on Claude and AWS Bedrock, MCP servers that let AI operate your product, real-time market data pipelines and SaaS on AWS.

Get your free roadmap See our work
  • Roadmap in 48 hours
  • NDA on request
  • You own 100% of IP
  • US hours overlap
MCP tools behind one desktop AI agent
105
automated tests on a voice AI product
1,500+
live analytics pages in production
130+
Redis keys served in a hardened cluster
10M+

Products we've built for

All client projects

Production experience with

  • Claude & AWS Bedrock agents
  • MCP servers
  • US options (OPRA) data
  • Real-time WebSockets
  • Stripe billing
  • Signed desktop apps
  • Voice AI
  • AWS & Kubernetes
  • Claude
  • AWS Bedrock
  • OpenAI
  • Gemini
  • LangGraph
  • LangChain
  • DeepAgents
  • LangFuse
  • MCP
  • RAG
  • ElevenLabs
  • Hugging Face
  • Stable Diffusion
  • Python
  • Django
  • DRF
  • Django Channels
  • FastAPI
What we build

Five specialties.
One senior team that ships them.

We go deep instead of wide: AI agents, MCP servers, real-time market data, voice AI and the SaaS infrastructure underneath them.

All services
Interactive demo

Ask our agent how we’d build it

Pick a prompt or type your own. The agent searches our shipped work, then answers with an architecture, a timeline and the proof behind it.

zerotwo-agent — scoping sessiondone
>Scope an AI agent for my SaaS
search_case_studies(query="ai agent saas")
2 matches: AI research agent (16 tools, 8 versions) · Voice AI assistant (56 tools)
get_service(slug="ai-agent-development")
stack: Anthropic Claude, AWS Bedrock, OpenAI, Gemini, LangGraph +7
*Thought for 1.4s · Mapping your product's actions to typed tools

Start with one deep agent on Claude via AWS Bedrock that calls your product through typed, permission-checked tools. Anything numeric runs in a deterministic engine the agent calls as a tool, so figures are never hallucinated. It ships with streaming, LangFuse tracing, an evaluation set and per-request cost metering from day one.

Suggested architecture

  1. Your app
  2. WebSocket streaming
  3. Agent loop · Claude on Bedrock
  4. 5–15 typed tools
  5. Postgres state
  6. LangFuse traces

Timeline

Technical roadmap
48 hours
Discovery sprint
1–2 weeks · architecture, tool list, eval set, prototype on your data
Production pilot
4–8 weeks for a focused agent with 5–15 tools
After launch
Weekly demos, regression evals on every release

Shipped before: an AI research agent on Claude via AWS Bedrock with 16 tools, taken through 8 versions in production.

→ Get this as a written roadmap

Scripted demo. Real agents run on your data.

Selected work

Systems running in production,
not slideware.

Four connected products we engineered for an options analytics company: a web platform, a market data pipeline, a desktop AI app and a voice assistant. Client names are withheld under NDA.

FinTech · Trading analytics

AI research agent for an options analytics platform

A subscription analytics platform with 130+ live pages for options flow, dark pool and volatility data, plus an AI research agent on Claude via AWS Bedrock.

live analytics pages
130+
WebSocket routes
100+
agent tools
16
agent versions shipped
8
  • Django
  • DRF
  • Django Channels
  • Celery
  • PostgreSQL
  • Redis
Read the case study: AI research agent for an options analytics platform
FinTech · Market data

Real-time options flow and dark pool pipeline

A market data pipeline that ingests the US options (OPRA) firehose and dark pool trades without dropping messages during market-open bursts.

item bounded queue
50k
messages per batch write
5,000
  • Python
  • Redis Streams
  • RediSearch
  • WebSockets
  • Multithreading
  • AWS S3
Read the case study: Real-time options flow and dark pool pipeline
FinTech · Voice AI

Real-time voice AI assistant with 56 tools

A browser-based voice assistant with a live transcript, two voice engines behind one interface and metered usage billing, covered by 1,500+ automated tests.

voice-callable tools
56
automated tests
1,500+
  • Python
  • Django Channels
  • Celery
  • PostgreSQL
  • Redis
  • Gemini Live
Read the case study: Real-time voice AI assistant with 56 tools
All case studies Client projects with live links
Real-time by default

Market-open bursts, absorbed.

A live simulation of the options-flow pipeline we run in production: 200 ms burst buckets, a bounded 50,000-item queue and 5,000-message batch writes. Trigger a market-open spike and watch the queue soak it up, then drain, with zero dropped messages.

options-flow · OPRA30,855 ev/sSteady flow
  • Underlying price
  • Events per 200 ms bucket
  • Burst bucket
  • Queue depth vs 50k bound
Simulated data
Events processed
3,516,283simulated session total
p99 latency
5msfeed to WebSocket
Dropped messages
0alert fires on any drop
Queue depth
994/ 50,000303 batch writes of 5,000
Options printsSimulated data
  1. META10/16730Pblock$936Kbid
  2. QQQ10/09515Pblock$1.9Mask
  3. TSLA10/30330Psweep$246Kbid
  4. AMZN10/23220Psweep$271Kask
  5. AAPL10/16235Cblock$615Kbid
  6. QQQ10/23505Cblock$459Kask
  7. QQQ10/30515Csplit$284Kask
  8. QQQ10/30530Csweep$459Kmid

Modeled on our production OPRA and dark pool pipeline: bounded queues, pipelined batch writes, alerts on any dropped message and feeds that restart themselves when they stall.Read the case study

Why ZeroTwo

We remove the risks that sink AI projects

Most AI and FinTech builds fail in the same predictable ways. We engineer against each one by default.

Common riskHow we handle it
Impressive AI demo that breaks on real data Pilot sprint on your data and infrastructure before you commit
LLM invents numbers your users act on Deterministic calculation engines; the model explains, code computes
Surprise LLM bills Per-request cost metering, prompt caching and spend caps from day one
Junior team after the sales call Senior engineers on the call are the ones writing your code
Black-box code you cannot maintain Your repos, your cloud, tests and docs, 100% IP assignment
Messages dropped when traffic spikes Bounded queues, batch writes, burst detection and self-healing feeds
How we work

From first call to production,
with no surprises.

  1. 01

    Discovery call

    30 min

    We learn the business goal, constraints and what success looks like. NDA available before we talk details.

  2. 02

    Technical roadmap

    48 hours

    You receive architecture, milestones, risks and a fixed-scope proposal. No obligation.

  3. 03

    Pilot sprint

    1–2 weeks

    A working slice on your data and infrastructure, so you judge us on shipped software, not slides.

  4. 04

    Build & ship

    Weekly demos

    Weekly demos, written updates and staging you can click. Production releases behind CI/CD and tests.

  5. 05

    Run & scale

    Ongoing

    Monitoring, cost tuning and new features as a long-term engineering partner.

Our full process
Built for US teams

Your time zone. Your repos.
Your IP from day one.

We work the way US product teams already work: 4+ hours of daily overlap with US Eastern and Pacific time, weekly demos, written updates and contracts that assign every line of code to you.

New YorkET
ChicagoCT
DenverMT
San FranciscoPT

  • You own 100% of the IP

    Code lives in your repositories and cloud accounts from the first commit.

  • NDA before kickoff

    Mutual NDA on request before you share anything sensitive.

  • US business-hours overlap

    Daily overlap with Eastern and Pacific time for calls, reviews and incident response.

  • Weekly demos

    Working software every week, not status reports. Cancel any time with no lock-in.

  • Senior engineers only

    The people on the discovery call are the people writing your code.

  • Security by default

    Least-privilege IAM, secrets management, MFA and audit logs as standard practice.

Plan your build

Sketch your project. Get a realistic plan.

Pick what you are building and where you are today. You get a phase timeline, a team shape and the stack we would start from. No prices here: we quote a fixed scope after a short call.

What are you building?
What does it need?

Select all that apply.

Where are you today?
Your plan6–12 weeks to launch

Recommended engagement

Fixed-scope pilot

Best for: Validating an AI idea

A 1–2 week sprint with a fixed price that delivers a working slice. The lowest-risk way to start.

Phase timeline

  1. Discovery1–2 wks

    Architecture, risks and a working prototype

  2. Pilot1–2 wks

    A working slice on your data

  3. Build3–6 wks

    Weekly demos and a staging environment you can click

  4. Hardening1–2 wks

    Tests, monitoring, security baseline and launch

Team shape

AI lead + 2 senior engineers

Suggested stack

  • Claude
  • AWS Bedrock
  • LangGraph
  • LangFuse
  • Python
  • FastAPI
  • MCP
How we estimated this
  • AI agent baseline: build 2–4 wks, hardening 1–2 wks
  • +1–2 wks build · Integrations with existing APIs
Send this plan to our team

Indicative ranges. We confirm a fixed scope and price after a call.

FAQ

Frequently asked questions

Still have questions? Email info@zerotwosolutions.com and a senior engineer will reply within 1 business day.

What does ZeroTwo Solutions do?

ZeroTwo Solutions is a software development company specializing in production AI agents, MCP servers, real-time FinTech platforms and SaaS on AWS. We design, build and operate the software, from architecture to production.

Do you work with US companies?

Yes. Our engineering team is based in Surat, India, and works US hours: daily overlap with Eastern and Pacific business hours, US-English communication, NDAs and contracts that assign all IP to you. We do not have a US office, and we are upfront about that.

How quickly can you start?

Most clients get a technical roadmap within 48 hours of the first call, and pilot sprints typically start within one to two weeks.

What does a project cost?

We quote fixed-scope pilots and milestone-based builds after a short discovery call, so you see the full price before work starts. There are no long-term contracts.

What technologies do you use?

Python, Django, FastAPI, React, Next.js and TypeScript on AWS, with Claude, AWS Bedrock, OpenAI, Gemini, LangGraph and MCP for AI work, and PostgreSQL and Redis Streams for data.

Start a project

Have an AI or FinTech product to build?

Tell us what you want to ship. You will get a technical roadmap and a fixed-scope proposal within 48 hours.

Get your free roadmap info@zerotwosolutions.com
  • Reply within 1 business day
  • NDA on request
  • You own 100% of the IP