Meerkats AI
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Give AI the context behind your business.

We connect your data, definitions, state, rules and allowed actions into one governed context layer your AI agents can act on.Your team can ask business questions, trace answers back to the underlying data, and act with evidence.

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You've stacked skills files, DBs and agent harnesses on the latest model.

Now:

  • Your token bills are high.
  • Answers drift.
  • Automations break.
  • Your team finds no value.
  • You can't see what your agents did.
export_final_v3.csv
prompt_v12.txt
RIP

The latest LLM

2023 – next release

Smarter every release. Expensive. Still didn't know your business.

RIP

skills.md

last edited 9 months ago

Can't ensure accuracy. Nobody kept them current. Burns tokens.

RIP

Graph DB

Fortune 500? What are you doing here...

RIP

The agent harness

wired up last quarter

Connected every tool. Nobody could tell what it did.

Cut the noise. Get your context layer.

Models are built for everyone. Your business isn't. We help your LLMs know what changed, understand why, and decide what to do next.

  • Who & whatCustomers, accounts, products, people and teams.
  • Why & howThe jobs to be done, your workflows, and where each one is.
  • What's trueMetric definitions, rules and policies, written once.
  • WhenCurrent state, full history, and what changed since yesterday.
  • ConnectionsHow every customer, order, campaign and deal relates.
  • ActionsWhat agents may do, with permissions and limits.

It's great when your AI knows exactly what to do.

BeforeWithout contextCam 1
Reactionstandby
Contextnone
thinking
Thoughts
0
Actions
0
Outcome
…

We help you build the system that lets your agents see the whole context, examine it and decide on the right actions.

Spend far fewer tokens on every answer.

Your agents stop rereading raw rows, tool lists and docs on every call. We hand them just the context a task needs, so a small, fast model does the job.

Same question, two agentsIllustrative
You ask“Why did revenue drop last week?”
Agent on raw APIs0 tokens
Reads every row, every tool and the docs ≈ $0.00 per answer
Agent on Meerkats0 tokens
Reads the definition, three rows and the rule ≈ $0.00 per answer
100×fewer tokens for the same answer

Get the same right answer, every time.

On raw data, an LLM guesses what revenue means, which orders count and when your week starts. We give it your definitions and compute every number in code, so you get the right answer, traced to its source.

“What was revenue last week?”Same question
×LLM on raw data
Answer$468,920
  • ×Counted 312 cancelled orders
  • ×Left $31,400 of refunds in
  • ×Started your week on Sunday, in UTC
Off by $56,540
Ask again: $455,210
✓LLM with Meerkats
Answer$412,380
  • ✓Revenue = paid orders minus refunds
  • ✓Your week: Monday to Sunday, store time
  • ✓Computed in code from orders · synced 09:15
Matches your books
Ask again: $412,380

Automations that run your playbook the same way, every time.

Write your playbook in plain words. We turn it into a typed automation that runs on schedule, the same steps every time. Change a rule and your next run follows it.

Lead follow-upRuns daily · 9:00
1 · You writeEvery morning, give any lead with no owner for 24 hours to whoever is on call, and tell them in Slack.
2 · We runwhen   daily 09:00
if     lead.owner = none for 24h
do     assign → on_call
       notify → #sales
limit  10 leads per run
3 · Every day since
Mon…running
Tue
Wed
Thu
Fri

One system for every team and org, with the right access for each.

Give each team or partner its own workspace. You decide who sees what and which actions their agents can take. We log every change.

Brightloop Group3 workspaces
Meerkatsone shared context
WorkspaceGrowth team
ALM
Ads · Store · CRM
Read and write
WorkspaceOps
DS⚙
CRM · Slack
Read and write
Partner orgKestrel Labs
KR
Warehouse
🔒 Read only
Kai · Kestrel Labs tried to change an ad budgetBlocked · read only

Your AI keeps receipts. Every single one.

Every run prints a receipt: what it read, the rule it followed, what it changed and proof it worked. Open any run, any time.

MEERKATSRun #2481 · Lead follow-upToday 15:50
ReadCRM · Store · Slack
Data as of09:15
RuleFollow-up SLA v3
DecidedReassign 3 leads
Allowed byOps · limit 10/hr
Changed3 leads → on call
CheckedRead-back ✓
Tokens1,840
Time2.4s
Kept for your records

Use any agent or model. Change anything without a rebuild.

Claude, Codex, your own agents, n8n workflows and internal apps all read the same context from us over MCP and API. Swap the model, add an agent or edit a rule, and everything else keeps working.

Plugged in todayLive
  • Agents and apps
  • Claude Code
  • Codex
  • Your own agents
  • n8n workflows
  • Internal apps
Meerkatsone shared contextRules v3
  • Models
  • Claudein use
  • GPT
  • Gemini
  • Your own model
Edit a rule: the next run picks it up · Swap a model: same definitions, same answers

We've built the deep foundation for you to build reliable AI systems.

We've already built six layers: your data and integrations, one set of definitions, live context, stateful workflows, governed agent actions and a record of every decision. You build the AI systems your ecommerce, RevOps or ad ops teams need on top of it.

01 · Data & integrations
Connect the systems where the data lives

Ad platforms, marketplaces, store, payments, CRM, team channels, documents, warehouses. Synced on a schedule, re-read live before any action.

02 · Semantic layer
Every entity, metric and relationship defined once

One catalog maps platform labels to your definitions. Unknown names are refused, never guessed.

03 · Context layer
Data, knowledge, relationships, rules and current state

What exists, how it connects, what happened, what is true now, and what is allowed. Loaded by agents instead of rebuilt on every call.

04 · Stateful workflows
Responsibilities that remember

Typed contracts with triggers, windows, conditions and limits. They carry state across runs and give the same result for the same inputs.

05 · AI agents & actions
Agents reason over the context and act through connected systems

Claude, Codex, your agents and apps over MCP and API. Actions bind to a registry of typed, permissioned operations.

06 · Governance & traceability
Permissions, versioning, decision history

Who can do what, which rule version ran, and a record of every run with its inputs and read-back.

Bring the systems you already run on. We'll dig the tunnels.

Advertising, marketplaces, store, payments, CRM, team channels, documents, and any warehouse or API. Reads and writes, within the permissions you grant. Hover to see what each one adds.

AdvertisingMetaCampaign performanceGoogle AdsSearch & campaign performanceAmazon AdsSponsored ads performanceFlipkart AdsMarketplace ad performanceTikTok AdsVideo campaign performanceWalmart ConnectRetail media performanceBlinkitQuick-commerce ads & availabilityZeptoQuick-commerce ads & availabilityInstamartQuick-commerce ads & availability
BusinessShopifyOrders & revenueRazorpayPayments & refundsGA4Site behaviour & conversionsHubSpotLeads, deals & pipelineInventoryStock levelsWarehousePostgres, BigQuery, Snowflake tables
KnowledgeSlackTeam decisionsEmailClient instructionsDocumentsSOPs & playbooksAPIAny other system you run

Your AI agents can already access your data. We give them an understanding of your business.

You have the same models as everyone else. Let's give yours the context that's only yours.

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Questions from the surface, answered from below.

Still wondering whether Meerkats fits your stack? Start with one workflow and see it run on your own business context.

Book a demo

We give you the infrastructure to build AI systems that run your business operations, from ecommerce and ad ops to RevOps. At its core is the context layer your AI systems run on. It connects the systems where your business data and knowledge live, defines every entity, metric and relationship once, keeps current state and history, holds your rules, and exposes a fixed set of governed actions. Your agents read that context over MCP and API instead of reasoning over raw data.