VerveContext

Every answer, anchored to a source

Agents guess when they can't check. VerveContext grounds yours in 300+ live, verifiable sources — pulled at answer time, cited on the way out, and governed by keys you scope. Here's how a claim gets grounded, and what your agents can stand on.

  • Live pull
  • Cited claims
  • Audit trail
Get grounded→Browse sources
Why grounding

Three things a grounded answer gives you

Live where a model is frozen, cited where a model is confident, governed where a team needs control.

Current, not remembered

A model only knows what it saw in training, frozen at a cutoff. VerveContext pulls the fact live at answer time — so prices, weather, rates and news are as they are right now, not as they were the day training stopped.

  • Live pull
  • No cutoff

Every claim has a source

Each grounded fact comes back with the source it was pulled from — a provenance chip your agent can surface right next to the number. That's what turns a confident sentence into one a person can trace and trust.

  • Source chip
  • Traceable

Controls your team needs

One managed key, scoped per agent, with per-source usage and clear billing. Grant an agent only the sources it should reach, and see exactly what it pulled to ground each answer.

  • Scoped keys
  • Usage logs
How it works

How a claim gets grounded

Four steps between a question that needs a real number and an answer that can show its receipt.

  1. 01

    The agent asks

    A workflow reaches a point where the answer needs a real number — today's gold price, the weather in Tokyo, when a market opens. Instead of predicting it, the model calls the matching source as a tool.

  2. 02

    VerveContext pulls the live source

    The call hits the real, maintained source behind VerveContext at request time — median ~120ms — and returns a structured, typed value rather than scraped text.

  3. 03

    The fact returns with its provenance

    Every value comes back tagged with where it came from, so the origin travels with the number all the way to the model.

  4. 04

    The answer cites it

    The agent surfaces the claim with its source attached — a receipt a person or a downstream system can follow. Nothing is left as a confident guess.

The ground truth

What your agents can cite

300+ sources across the facts agents most often get wrong — each one a callable tool that returns a value with its origin.

Money & markets

Exchange rates, crypto and metal prices, stock indices and earnings — the numbers agents most often get wrong when they guess.

  • exchangerate
  • goldprice
  • stockindex

Weather & environment

Conditions, forecasts, marine and air-quality readings for any location — grounding for logistics, travel and ops agents.

  • weather
  • marineweather
  • airquality

Places & geo

Geocoding, timezones, distances, demographics and cost-of-living to anchor any location-aware reasoning.

  • reversegeocode
  • timezone
  • costofliving

News & world

Current headlines, historical events, holidays and world time — context a model can't infer on its own.

  • worldnews
  • worldholidays
  • worldtime

Web & domains

DNS, WHOIS, SSL and reputation lookups to ground security, compliance and research workflows.

  • dnslookup
  • whois
  • sslchecker

Language & text

Translation, sentiment and text analysis to normalize and verify the language flowing through your agents.

  • translator
  • sentiment
  • textsummarizer

Grounding, in practice.

How teams put VerveContext behind their agents.

The concept, explained →
What does it mean to "ground" an agent?
Grounding means anchoring the agent's answer to a real, checkable fact fetched at answer time — instead of letting the model predict a plausible-sounding value from training memory. With VerveContext, the agent calls a live source, gets back a typed value with its origin, and cites it.
How is this page different from "What is grounding?"
This page is about how VerveContext grounds your agents in practice — the live pull, the provenance chip, the enterprise controls. If you want the concept explained from scratch — why models hallucinate, how grounding differs from RAG and fine-tuning — read What is grounding?, the concept explained.
Does grounding slow the agent down?
A grounding call returns in roughly 120ms at the median, and the agent only calls a source when an answer actually needs a real value. The alternative — a confident wrong number a person has to catch and correct later — costs far more.
Can I control which sources an agent can reach?
Yes. Keys are scoped, so you grant an agent only the sources it should be able to pull, and every call is recorded in usage and audit logs. See the governance page for how scoped keys and logs work.
What shows on my bill?
VerveContext runs on APIVerve, our production data engine, so invoices and card statements read APIVERVE. Same account, same key, same rails — nothing else changes.

Give your agents something to stand on. Connect over MCP, enable your sources, and every answer comes with its receipts.

Get grounded→Compare approaches

Browse the sources

See the 300+ live, verifiable sources your agents can stand on.

Source registry