AI & software engineering studio · Production AI, automation, and systems built to scale

AI IMPLEMENTATION STUDIO

Find where AI pays off.
Then build it.

We build AI solutions and scalable software for businesses — agents, automation, and production-ready systems designed to solve real workflows and grow with you.

Accurate AI with built-in safety checks

Enterprise software that scales with your AI

Secure, private, and audit-friendly

EXAMPLE — LEAD PIPELINE

Illustration

Incoming Lead

Pricing page visitor

SaaS Company · 48 employees · viewed pricing 3×

acme.coDemo requested

AI RESEARCH ENGINE

Intent Score

94/100

Company Fit

High

Buying Signal

Strong

CRM → Enrichment → Slack → Outreach

Qualified Pipeline

Routed to sales in 42 seconds

TOOLS WE USE TO BUILD & RUN PRODUCTION SYSTEMS

Anthropic Claude 3.7 / 3.5Frontier LLM
OpenAI GPT-4oMultimodal AI
Google Gemini 2.0Fast Inference
LangGraph & SwarmsAgent Orchestration
FastAPI & Python 3.12Async Backend
Next.js 16 & React 19Enterprise Web
TypeScriptTyped Application Layer
JavaScriptFull-Stack Runtime
Go (Golang)High-Performance Backend
PostgreSQL / pgvectorHybrid Vector DB
Redis & Distributed LocksIn-Memory Cache
Apache Kafka & Event QueuesDistributed Streaming
Temporal.io & Async WorkersStateful Workflows
Docker & KubernetesMicroservices
AWS & GCP Cloud VPCEnterprise Infra
OpenTelemetry & TracingObservability
Anthropic Claude 3.7 / 3.5Frontier LLM
OpenAI GPT-4oMultimodal AI
Google Gemini 2.0Fast Inference
LangGraph & SwarmsAgent Orchestration
FastAPI & Python 3.12Async Backend
Next.js 16 & React 19Enterprise Web
TypeScriptTyped Application Layer
JavaScriptFull-Stack Runtime
Go (Golang)High-Performance Backend
PostgreSQL / pgvectorHybrid Vector DB
Redis & Distributed LocksIn-Memory Cache
Apache Kafka & Event QueuesDistributed Streaming
Temporal.io & Async WorkersStateful Workflows
Docker & KubernetesMicroservices
AWS & GCP Cloud VPCEnterprise Infra
OpenTelemetry & TracingObservability

WHAT WE DO

AI first — with the software to run it in production.

Agents and automation are the focus. We also build the enterprise apps, APIs, and infrastructure that make AI reliable day after day.

Talk through your project
Assistants, automation & search

1. Smart AI Products

Custom AI that answers questions, completes tasks, and connects to your data — with checks in place so answers stay accurate and actions stay controlled.

What you get:

  • AI assistants that take action in your tools
  • Search across your docs and knowledge base
  • Safety checks before anything is sent or saved
  • Testing before launch so quality stays high
Production backends & integrations

2. Software That Powers AI

The enterprise software behind your AI — APIs, background jobs, and integrations that keep agents reliable under real traffic and busy periods.

What you get:

  • Infrastructure that keeps AI running in production
  • Background jobs for long-running AI workflows
  • Queues so nothing is dropped under load
  • Connections to CRM, Slack, databases, and your stack
Deploy, monitor & improve

3. Launch & Hosting

We launch your system on secure cloud infrastructure, set up monitoring, and ship updates without taking your product offline.

What you get:

  • Cloud deployment on AWS or GCP
  • Monitoring and alerts when something breaks
  • Safe updates without downtime
  • Infrastructure that grows with demand
Portals, dashboards & secure connections

4. Enterprise Apps & Integrations

Web apps, admin dashboards, and connections to CRM, Slack, email, and databases — with role-based access and clear audit trails.

What you get:

  • Modern web apps your team can use daily
  • Login, permissions, and access control
  • Private hosting and encrypted data
  • Your data is never used to train public models

WHY PROJECTS STALL

Most AI projects stop at the demo stage.

A quick prototype is easy. A system your team can trust needs accuracy checks, reliable infrastructure, cost control, and real integrations.

Typical AI Demo

AI demos that sound smart but fail in production
Agents that give confident but wrong answers
AI that slows down or breaks when usage grows
Runaway AI costs with unclear business return

How Northloop Builds

Production AI with testing, safeguards, and real business integrations
Built-in checks so outputs are validated before they reach customers
Enterprise software and architecture built to scale with demand
Smart design that keeps running costs predictable and tied to outcomes

EXAMPLE WORKFLOWS

How we design production AI agents.

Switch scenarios to see the kind of workflows we build for sales, support, and document tasks. These are illustrative examples — not a live system, real client data, or real-time AI.

Transparency note: Sample scenarios and sample metrics used to explain our process. No AI runs on this page, and nothing here is presented as a client result.
Example trigger / inbound eventLead Scoring

Analyze 50 inbound leads from yesterday, score intent & route high-value accounts.

Model routingFast Classifier (Gemini Flash) → Reasoning (Claude 3.5 Sonnet)

Example workflow steps

1. Ingest & Context Enrichment

Enriched in 48ms

Ingested webhook, enriched Clearbit domain data, checked 14-day pageview logs.

2. Context Filter & Intent Scoring

Score: 94/100

Evaluated ICP criteria (B2B SaaS, >40 headcount, pricing visits >= 3).

3. Safety Harness & Validation

Passed 100%

Verified CRM deduplication key; checked anti-spam compliance policy.

4. Autonomous Downstream Action

Slack & HubSpot synced

Drafted personalized executive briefing + dispatched high-priority Slack deal alert.

Sample outputExample result & metrics

Execution Latency

410ms

Cost per Run

$0.0028 vs $0.09 naive

Accuracy Score

98.4%

Guardrail Status

Active & Verified

3 Enterprise Accounts Dispatched to Sales Owners

Identified high-buying-signal enterprise accounts with immediate budget authorization.

Top Match

Acme Cloud Corp (Score 96)

Buying Signal

3x Pricing page + Legal terms viewed

Routed To

Sarah K. (Senior AE)

Example actions in this workflow

  • Enriched tech stack & executive team via Clearbit
  • Created qualified deal stage in HubSpot CRM
  • Dispatched Slack alert to #sales-enterprise with customized talking points
Built for accuracy, review, and audit trailsDiscuss a real build for your team

HOW WE WORK

A clear 10-step process from idea to live product.

Every step has a defined goal and deliverable — so you always know what we're building, testing, and shipping next.

OUR 10-STEP BUILD PROCESS

Click any step to see the goal, deliverable, and how we reduce risk

05

Stage 05: Build

Turnaround: 1-2 weeks

What we aim for

Build the product — AI logic, dashboards, and connections to your tools.

What you receive

Working software connected to your stack (CRM, Slack, database, etc.).

How we reduce risk

Built to handle real traffic with background jobs and secure APIs.

KEEPING AI COSTS UNDER CONTROL

Smarter AI use = lower monthly costs.

Feeding the AI everything at once is expensive and often makes answers worse. We pull only what's relevant, cache what repeats, and route simple tasks to cheaper models — so you get better results for less.

Example comparison — not a specific client result.

High confidence → act automatically · Low confidence → send to a person

BASIC SETUP

~4× the AI usage

Slower responses

Higher monthly bill

More noise, less accuracy

OPTIMIZED APPROACH

~76% less usage

Faster responses

Lower monthly bill

More relevant, accurate answers

ROI & PAYBACK CALCULATOR

Calculate your automation leverage.

See exactly how much manual repetitive workflows cost your company and the projected net ROI from production AI systems.

Average client payback: Under 7 weeks
12 people
2 members30 members60+ members
10 hrs/wk
4 hrs (light)12 hrs (typical)25 hrs (heavy ops)
$55 / hr
$25/hr (Junior ops)$60/hr (Mid SDR/Specialist)$140/hr (Senior Engineer/Lead)
Target Workflow Automation Rate:75% automated
PROJECTED FINANCIAL RETURNAnnual Model

Net Annual Value Created

$227,700 / yr

Net of model inference costs, vector storage, and continuous evaluation harness.

Work Hours Reclaimed

4,500 hrs

Redirected to strategic revenue

Estimated Payback Period

~1.3 Months

Full project cost breakeven

Current Manual Drain

$330,000 / yr

Wasted in manual copy-paste

AI Cloud & Token Cost

~$19,800 / yr

Optimized with model routing

Claim Your Free Workflow ROI Audit
We teardown your actual process & give you an architectural spec

SELECTED WORK

Real systems, honestly labeled.

Client builds, engineering case studies, and internal R&D — each with the architecture, decisions, and tradeoffs behind it. No invented clients. No fabricated metrics.

Explore all work

Could one of these be relevant to your business? See how we'd approach it →

Client Voices

Trusted by teams shipping real products.

From AI agents to full marketplaces — hear from clients who needed production systems, not demos.

We needed a real marketplace — not another inspiration feed. Northloop shipped the full vendor platform: paid bookings, per-order chat, wallet credits, and Canadian bank payouts. Vendors can sign up today and run their entire event business in one place.

PL

Partylist Team

Event Vendor Platform · Canada

Marketplace · Bookings · PayoutsVisit Partylist

ENGAGEMENT ROADMAP

Clear, transparent ways to work together.

No bloated agency retainers without deliverables. Fixed timelines, clear milestones, and 100% IP ownership.

NDA-protected · Full Code Ownership · Zero Vendor Lock-in
Sprint 0 1 – 2 Weeks

AI Opportunity Audit & Blueprint

Founders & CTOs who need clarity on where AI actually delivers positive ROI before building.

What you receive:

  • Workflow teardown & data readiness audit
  • Deterministic vs Agent boundary architecture
  • Interactive proof-of-concept / clickable prototype
  • Token cost model & expected ROI payback timeline
  • Comprehensive implementation blueprint with OpenAPI schemas
Client Time Needed:Two 45-min kickoff interviews with your team leads
Book an Audit Sprint
RECOMMENDED FOR MOST TEAMS
Most Popular 3 – 4 Weeks

Production System Implementation

Companies ready to ship a fully functional, production-ready AI agent or automated workflow.

What you receive:

  • Full-stack agent engine (FastAPI / Next.js / Python / Postgres)
  • Strict context engineering & semantic retrieval pipeline
  • Deterministic safety harness (schema validation, fallbacks, retries)
  • Automated evaluation suite (100+ edge-case test fixtures)
  • Bidirectional integrations (Slack, HubSpot, Salesforce, Zendesk, ERP)
  • Full source code ownership + containerized deployment
Client Time Needed:Weekly sprint check-in + acceptance testing
Build Production System
Long-term Scale Monthly Retainer

Managed AI Partner & Evolution

Fast-growing teams needing continuous monitoring, model fine-tuning, and token cost pruning.

What you receive:

  • 24/7 telemetry & observability monitoring (latency, cost, accuracy)
  • Continuous prompt & context pruning to reduce inference bills
  • Model router updates as new frontier models (Claude 3.7, GPT-4.5) drop
  • Ongoing synthetic regression testing on all workflow changes
  • Dedicated senior AI engineering hours & priority Slack channel
Client Time Needed:Bi-weekly roadmap review & performance sync
Partner With Us

LET'S BUILD SOMETHING THAT PAYS OFF

Book a free 30-minute discovery call.

Walk us through your workflow and we'll give you an honest feasibility read, architecture direction, and fixed-price scope — no sales pitch.

24-hour follow-up

Senior AI engineers — not generic sales.

NDA protected

Bilateral NDAs before discussing proprietary workflows.

Prefer email?

ashu.satapathy2002@gmail.com

Pick a time that works for you

30-minute discovery call

Walk through your workflow with us

Free architecture review — no sales pitch. Pick a slot that works for you.

30 minutes · video call
Google Meet or Zoom
Or open calendar in a new tab