panabot
CALIBRATING OPTICS_
BOUTIQUE AI & SOFTWARE ENGINEERING

Software that sees.
Systems that ship.

Panabot designs and builds AI solutions, data automation, SaaS products, custom web platforms, and mobile apps — engineered like it matters.

See our work
TRUSTED BY TEAMS BUILDING WITH US
NORTHLINEvectorlabsOSSIA_HELIXmarrow&co
* placeholder logos — swap with real clients
AI SOLUTIONSDATA MINING & SCRAPINGSAAS DEVELOPMENTWEB · CMS · CRMMOBILE APPS
AI SOLUTIONSDATA MINING & SCRAPINGSAAS DEVELOPMENTWEB · CMS · CRMMOBILE APPS
0+
Products shipped to production
0M
Records processed daily
0.00%
Pipeline uptime, trailing 12 mo
0.0/5
Average client rating
* sample figures — replace with production metrics
01 — SERVICES

Five disciplines.
One engineering standard.

ALL SERVICES →

AI Solutions

AI bots are our core craft — agents, assistants, and chatbots that ship to production, not demos that stall in a notebook.

LLM integration & RAG pipelines
AI bots, agents & assistants
Custom ML models & chatbots
Intelligent automation
−80% manual triage *

Data Mining & Scraping Automation

Resilient, large-scale extraction that never sleeps.

Distributed scrapingCleaning & enrichmentETL pipelines120M records/day *

SaaS Development

From MVP to platform, without the rewrite.

Architecture · Dashboards
Billing & multi-tenancy
6 wks to v1 *

Web, CMS & CRM

Bespoke platforms shaped to how you actually work.

Custom web apps · Headless CMS
Tailored CRM systems
3× faster ops *

Mobile App Development

Native feel, cross-platform reach, zero jank.

Native & cross-platformClean UX4.8★ store rating *
02 — PROCESS

Four steps. No surprises.

STEP 01

Discover

We map the real problem, the data, and the constraints before anyone writes code.

↳ Technical roadmap
STEP 02

Architect

System design reviewed with your team — boring where possible, novel where it pays.

↳ System design doc
STEP 03

Build

Short cycles, working software every week, instrumented from the first deploy.

↳ Shipping product
STEP 04

Scale

Hardening, load, cost tuning, and a team that knows how to run what we built.

↳ SLOs & runbook
03 — SELECTED WORK

Problems, solved on the record.

* placeholder clients & metrics
DATA AUTOMATION

Northline Logistics *

PROBLEM · 40 analysts hand-copying carrier data from 300+ portals.
SOLUTION · Distributed scraping fleet with drift detection and enrichment.
Cut manual data ops by 80% *
SAAS RE-ARCHITECTURE

Vector Labs *

PROBLEM · MVP buckling past 10k users; releases frozen for months.
SOLUTION · Incremental re-architecture with zero-downtime migration.
11× throughput, weekly releases *
AI ASSISTANT

Marrow & Co *

PROBLEM · Support backlog growing faster than the team.
SOLUTION · RAG assistant over 40k docs with human handoff built in.
62% of tickets auto-resolved *
04 — TOOLING

A stack chosen, not collected.

25 MODULES · OPERATIONAL
panabot://stack.sys
HOVER TO INSPECT_
[01]AI / ML
anthropic
openai
pytorch
langchain
weaviate
[02]DATA
python
scrapy
airflow
dbt
postgres
[03]WEB
typescript
react
next.js
node
graphql
[04]MOBILE
swift
kotlin
react-native
flutter
expo
[05]CLOUD
aws
gcp
kubernetes
terraform
cloudflare
// boring where possible, novel where it paysv2026.07 · audited quarterly
05 — WHAT CLIENTS SAY

"They rebuilt in four months what our previous vendor couldn't stabilize in two years — and the pipeline hasn't dropped a record since."

MK
M. Keller *
VP Engineering, Northline

"The rare agency that argues you out of features you don't need."

S. Adeyemi *
Founder, Vector Labs

"Our AI assistant went live in six weeks and now resolves most support tickets before a human sees them."

J. Marrow *
COO, Marrow & Co
06 — INSIGHTS

Notes from the build floor.

ALL INSIGHTS →
JUL 2026 · 6 MIN READ

Why most RAG pipelines fail after the demo

Retrieval quality decays quietly. Here is the evaluation harness we ship with every assistant.

READ →
JUN 2026 · 4 MIN READ

Scraping at 120M records a day without getting blocked

Adapters, drift detection, and the boring infrastructure that keeps pipelines alive for years.

READ →
MAY 2026 · 5 MIN READ

The MVP-to-platform rewrite you can skip

Architecture decisions that let a weekend prototype survive its first 100k users.

READ →
07 — FAQ

Questions we hear a lot.

Everything else is a 30-minute call away — no pitch deck, just a senior engineer with questions.

Ask us directly
How do engagements start?

With a paid 1–2 week discovery: we map the problem, the data, and the constraints, and hand you a technical roadmap you can execute with us or without us.

What does a typical project cost?

Discovery is fixed-price. Builds typically range from focused automations to full platforms — after discovery you get a scoped estimate, not an hourly black box.

Who actually does the work?

Senior engineers only. The people on your first call write the code. No outsourcing, no junior bench learning on your budget.

Can you work with our in-house team?

Yes — we regularly embed alongside internal teams, pair on architecture, and hand over with docs, runbooks, and recorded walkthroughs.

Who owns the code and the models?

You do. Full IP transfer, your repositories, your cloud accounts. We keep nothing hostage.

How do you keep AI systems accurate?

Every AI build ships with an evaluation harness, fallback paths, and observability — accuracy is measured continuously, not assumed.

08 — WHO WE ARE

A small team that builds like it owns the outcome.

Senior engineers only. No account-manager relay, no junior bench learning on your budget. The people you meet on the first call are the people who ship your system.

MORE ABOUT US →
92%
of our work comes from referrals
and repeat clients *

Have a system worth building?
Let's talk.

Reply within one business day.