The knowledge that keeps you anchored, always accessible

Your company’s own Brain wired on your data

Anchorlog is a centralized knowledge platform that turns your company’s institutional memory into instant, accurate answers through an AI chatbot. Decisions, product data, procurement history, founder level judgment: all of it becomes searchable. Your team handles quotations, product lookups, sales FAQs and procurement planning without digging through spreadsheets or waiting on a senior colleague, so knowledge is preserved as the business grows.

Built by people who ran a factory. Working prototype, alpha-tested in our own plant. One pilot completed, a second in progress.

Assistant

Calculate shipping for 50 hoodies to the USA

Shipping_and_Logistics.pdfsection 3

$430.86 using Via NL DDP, on a chargeable weight of 43 kg.

  1. 1Hoodie, from the weight database: 0.8 kg
  2. 250 × 0.8 = 40 kg, +7% packaging = 42.8 kg
  3. 3Rounded up to 43 kg → bracket 40–49
  4. 4Over 32 kg → Via NL DDP at $10.02/kg

What changes with Anchorlog

The same work, done the way it is done today and the way it is done once your documents can answer for themselves.

Quotations

Hours, and varies by who builds it

Anchorlog: Seconds, consistent every time

Product lookups

Digging through files or asking a colleague

Anchorlog: Plain-language answers from your records

Sales FAQs

Same answers repeated all day

Anchorlog: Always-on, consistent answers

Procurement

Locked in one manager's memory

Anchorlog: Vendor history and buying judgment for anyone

Founder judgment

Every edge case waits for the founder

Anchorlog: Available to the whole team, anytime

Staff turnover

Knowledge leaves with people

Anchorlog: Knowledge stays with the company

What you are using today, and where it stops.

None of these are wrong. Every one of them is already in your business and doing a job. The question is what happens when someone needs a number that lives inside one of them.

Generic LLMs (ChatGPT, Gemini, Claude)

Broad general knowledge, but no ongoing access to your costing, vendor history, or past decisions; answers depend on what someone uploads each session

Anchorlog: Wired to your company's own data, so answers reflect how your business actually prices, buys, and decides

ERP systems (SAP, Odoo, Oracle)

Store transaction records, but not the reasoning behind decisions; expensive, slow to implement, and hard to query for everyday questions

Anchorlog: Captures the “why” behind decisions and makes it answerable in plain language, without a months-long rollout

Building an in-house AI tool (developers or agencies)

High upfront cost, long build time, and needs ongoing maintenance; most developers don't understand manufacturing data

Anchorlog: Ready-made for manufacturers, with the industry understanding already built in

Spreadsheets, shared drives, and email

Scattered, inconsistent versions across teams; finding anything means digging or asking someone

Anchorlog: One centralized, searchable source of truth across sales, production, and procurement

WhatsApp groups and chats

Critical decisions, prices, and approvals get buried in endless threads; nothing is searchable or organized, and it leaves with the person's phone

Anchorlog: Turns scattered conversations and decisions into organized, permanent company knowledge

Relying on the founder and senior staff

Creates bottlenecks, slows new hires, and knowledge leaves when people do

Anchorlog: Makes their judgment available to everyone, anytime, and keeps it in the company permanently

One engine. A pack per industry.

The hard part is industry-agnostic: pulling documents in, keeping a knowledge base current, orchestrating the model. We built that once. What differs between a factory and a clinic is vocabulary, calculators, compliance rules and the questions people ask on day one. That is configuration, not a rebuild.

The engine

  • IngestionPDF, Word, Excel, CSV with tables kept intact
  • Knowledge basechunked, embedded, searchable
  • Re-indexingreplace a document, the answers change with it
  • Orchestrationretrieval, grounding, citation

Built once, shared by every pack. WhatsApp and Drive connectors are specified and in build.

Manufacturing
Apparel & textile export
Sports goods
Surgical instruments
Retail & distribution
Clinics
Logistics
Contractors

Eight industries that run the same way.

Documents nobody can find, and the answers living in one person’s WhatsApp. The shape of the problem is identical. Only the vocabulary changes.

IndustryWhat the pack knowsStatus
Manufacturingcosting sheets, SOPs, machine specs, FOB pricingRunning
Apparel & textile exportMOQ, lead times, size charts, freight, IncotermsLive in this demo
Sports goodsball specs, FIFA test criteria, stitching rates, OEM minimumsPack defined
Surgical instrumentsISO 13485 files, CE and FDA paperwork, steel grades, instrument specsPack defined
Retail & distributionprice lists, stock, dealer terms, credit limitsPack defined
Clinicsschedules, procedure prep, insurance rulesPack defined
Logisticsrate cards, transit times, surcharges, detentionPack defined
ContractorsBOQs, site specs, subcontractor ratesPack defined

“Running” means a pilot customer with their own documents connected. One pilot is completed and a second is in progress. “Live in this demo” means the assistant on this site is loaded with that industry’s real documents right now. “Pack defined” means the vocabulary and calculators exist and nobody is using them yet.

Measured in a working factory, not on a slide.

30 min → 10 sec

per buyer quotation

Quotation preparation time

21 hrs

per week, sales team

Hours given back to the people doing the work

5000+

in the factory and the pilot

Operational questions answered from documents

From our own factory and the first completed pilot. A second pilot is in progress; we will update these when it closes.

Thirty minutes became ten seconds.

The single measurement behind the first figure above: how long it took to put a price in front of a buyer, before and after. The work did not get easier. The looking up stopped.

View as table
Time to quote a buyer, in minutes
StageMinutes
Before AnchorLog30
With AnchorLog0.17

Built by the people who were doing the three hours.

Abdul Rehman Kazi spent eight years running a manufacturing business, seven of them stuck in this loop, and holds a BS in Computer Science. His cofounder, Muhammad Umer Nadeem, builds the engine.

The alpha ran in our own factory, on our own costing sheets, answering our own buyers’ questions. That is why it will tell you a minimum order quantity and name the sheet it read it from, instead of inventing a number that sounds right.

There are 23,000 registered companies in Sialkot. We are going after 5 per cent of them, 1,150 companies, by mid-2027.