Newton on Mars — AI-Powered Project Scoping & Consultancy

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AI Agent Engineering

Streaming chat & voice interfaces bounded by truth.

General-purpose chatbots often fall short in professional environments. We build domain-specific AI agents that operate precisely within defined parameters, integrating seamlessly with your business logic.

From sub-500ms voice agents to robust multi-turn chat applications, our solutions never hallucinate pricing features, or policies. They are built on fast async backends, maintaining state across highly concurrent connections.

Key Capabilities

✓Sub-500ms streaming voice agents (STT/TTS)
✓Multi-agent orchestration and delegation
✓Strict guardrails and conversation routing
✓Parallel tool calling and API interactions
✓Cost predictability & observability

TL;DR / Key Takeaways

→We replace rigid contact forms with flowing agentic intake.
→Built on FastAPI for superior Python async latency.
→Strict fallback mechanisms guard against LLM drift.

How It Works

StrategyDefine core capabilities and guardrails.

BuildDevelop async routing and strict tool calls.

DeployPush to AWS/Vercel with load balancing.

OptimizeAdjust latency thresholds and prompts based on user interaction logs.

Use Cases

Interactive Sales QualificationCapture lead details natively via conversation.

Automated Dispatch SupportVoice-led intake for high-volume logistics.

Metrics

52% Call Time ↓3× Qual. Leads

Tech Stack & Tools

FastAPIGroqOpenAI RealtimeWebSocketsSSE

Case Study Preview

FINANCE

How a Mid-Market AP Team Cut Invoice Cycle Time by 85% Without Replacing Their ERP

An agentic invoice processing system that ingests, extracts, three-way matches and routes invoices for human review — without touching the client's existing ERP.

85%FASTER CYCLE TIME

CUSTOMER EXPERIENCE

Auditing 100% of Support Calls Instead of 2%, in Minutes Rather Than Months

An always-on contact-centre QA agent that transcribes, scores and risk-flags every call across a 120-agent floor — moving the QA team from sampling to curation.

100%CALL COVERAGE

CONTENT & BRAND

An In-House Writing Co-Pilot That Sounds Like the Brand, Not the Model

A retrieval-grounded writing co-pilot that scored every draft against brand pillars and cited the assets behind every line — earning a brand team's trust.

6.8xWRITER OUTPUT PER WEEK

— 01

AI Agent Engineering

Streaming chat & voice interfaces bounded by truth.

Key Capabilities

✓Sub-500ms streaming voice agents (STT/TTS)
✓Multi-agent orchestration and delegation
✓Strict guardrails and conversation routing
✓Parallel tool calling and API interactions
✓Cost predictability & observability

TL;DR / Key Takeaways

→We replace rigid contact forms with flowing agentic intake.
→Built on FastAPI for superior Python async latency.
→Strict fallback mechanisms guard against LLM drift.

How It Works

StrategyDefine core capabilities and guardrails.

BuildDevelop async routing and strict tool calls.

DeployPush to AWS/Vercel with load balancing.

OptimizeAdjust latency thresholds and prompts based on user interaction logs.

Use Cases

Interactive Sales QualificationCapture lead details natively via conversation.

Automated Dispatch SupportVoice-led intake for high-volume logistics.

Metrics

52% Call Time ↓3× Qual. Leads

Tech Stack & Tools

FastAPIGroqOpenAI RealtimeWebSocketsSSE

Case Study Preview

FINANCE

How a Mid-Market AP Team Cut Invoice Cycle Time by 85% Without Replacing Their ERP

An agentic invoice processing system that ingests, extracts, three-way matches and routes invoices for human review — without touching the client's existing ERP.

85%FASTER CYCLE TIME

CUSTOMER EXPERIENCE

Auditing 100% of Support Calls Instead of 2%, in Minutes Rather Than Months

An always-on contact-centre QA agent that transcribes, scores and risk-flags every call across a 120-agent floor — moving the QA team from sampling to curation.

100%CALL COVERAGE

CONTENT & BRAND

An In-House Writing Co-Pilot That Sounds Like the Brand, Not the Model

A retrieval-grounded writing co-pilot that scored every draft against brand pillars and cited the assets behind every line — earning a brand team's trust.

6.8xWRITER OUTPUT PER WEEK

What we build.

AI Agent Engineering

Key Capabilities

TL;DR / Key Takeaways

How It Works

Use Cases

Metrics

Tech Stack & Tools

Case Study Preview

How a Mid-Market AP Team Cut Invoice Cycle Time by 85% Without Replacing Their ERP

Auditing 100% of Support Calls Instead of 2%, in Minutes Rather Than Months

An In-House Writing Co-Pilot That Sounds Like the Brand, Not the Model

What else we build. Tight engagements, production outcomes.

What we build.

AI Agent Engineering

Key Capabilities

TL;DR / Key Takeaways

How It Works

Use Cases

Metrics

Tech Stack & Tools

Case Study Preview

How a Mid-Market AP Team Cut Invoice Cycle Time by 85% Without Replacing Their ERP

Auditing 100% of Support Calls Instead of 2%, in Minutes Rather Than Months

An In-House Writing Co-Pilot That Sounds Like the Brand, Not the Model

What else we build. Tight engagements, production outcomes.