Deep research on anything
Decompose any question across hundreds of sources. Cross-check and cite every claim
See the reportTrusted by teams that can't afford to get it wrong
Wisdom Ventures
Turn weeks of deal diligence
into an AI agent, in minutes
You define the diligence your team does by hand: the data room read, the comps build, the IC memo. Grep turns it into an agent that runs it on every deal, with every claim sourced back to a filing.
Objective & inputs
Diligence Voltaic AI before the Series B IC: traction, comps, and risks.
ContextVoltaic AI data roomIC memo template
Skills, assembled
Filing analysisComparables buildMemo synthesis
Filings & registriesMarket data
How this step works
You define the diligence your team does by hand: the data room read, the comps build, the IC memo. Grep turns it into an agent that runs it on every deal, with every claim sourced back to a filing.
Objective & inputs
Describe the work in plain language and attach your files. Grep reads them as context for the run.
Skills, assembled
Grep brings the right skill for each step, and generates new ones when the work is novel.
Cost & accuracy floor
Set a price ceiling and an accuracy floor. Grep designs the run to hold both. No prompts, no graphs.
An expert agent for every kind of work
Point Grep at the knowledge work that moves your business: research, diligence, sales, strategy, ops, monitoring.
Your agent workforce.
Create agents around your process. Run them across a list, on a schedule, or together on a larger assignment.
Custom agents. Your process, built in.
Give your agent instructions, files, and tools. Your team runs it from a form.
Onboarding policy.pdf
Company researchSubmitted
Company name
Acme Holdings Ltd
Instructions
Research ownership, screen for sanctions, and cite the source for each finding.
Example workspace
Your report is ready
Company profile, ownership, and source links.
One list. A result for every row.
Upload a list and run the same agent across every item in parallel.
Companies.csv3 / 3
| Company | Status | Result |
|---|---|---|
| Acme Holdings Ltd | Completed | Report |
| Cedar Technologies | Completed | Report |
| Northstar Trading | Completed | Report |
Example workspace
Batch complete
3 companies researched. 3 reports ready.
Keep watch. Get the update.
Run on a schedule, or let a monitor alert you when something changes.
Competitor newsActive
- What to watch
- Product launches and pricing changes from the companies on my watchlist.
- Check frequency
- Every weekday · 9:00 AM
- Deliver to
- Inbox and email
Example workspace
Competitor news
Just now
1 new finding · A new pricing page was published.
Several agents. One complete output.
Split an assignment across agents, run the jobs in parallel, and combine their findings.
Research Acme Holdings. Combine ownership, sanctions, and news into one output.
Acme Holdings Ltd
Two beneficial owners identified. No sanctions matches found. One recent acquisition reported.
Sources1Company registry2Screening results3News coverage
Example workspace
Research complete
3 agent results combined into one output.
Your work. Your format.
Get results ready to read, present, share, or use in another system.
- Report
- Doc
- Deck
- Sheet
- Database
- HTML
- Dashboard
- Audio / Video
- JSON
An Operating System for all your agents
The pieces most teams cobble together by hand: orchestration, routing, sandboxing, retries, billing, data access. Managed for you, enterprise-grade by default.
One system. Every agent.
Agent OS
From the first instruction to every production run.
Agent brain
Orchestrates and routes tasks across agents with quality-aware model selection: the right model for each step, every time.
Model optimization
Fine-tuned secure open-source models picked for cost/performance per task. Frontier is reserved for the judgment calls.
Sandboxed execution
An isolated environment for every run. Untrusted code and tool calls execute with zero risk to your infrastructure.
Control plane
Jobs, retries, outputs, billing and observability, with a full auditable trace of every step, tool call and model used.
Data integrations
100+ pre-wired sources across finance, legal, business intelligence and news, plus a permissioned path to your own data.
Cost controls
Set spending limits for each run and track usage costs across your agents.
Role-based access control
Assign permissions by role to control access to reports, API keys, and user management.
Scoped keys
Per-workflow credentials, least-privilege by default. Rotate or revoke without downtime.
Decision-trail export
Every model choice, cost and reason, exportable as a file you can hand to a regulator.
SOC 2TYPE II
Type II in progress, report on request. Annual penetration testing by third party.
Data handling
No training on your data. Configurable retention. Delete on request, verifiably.
Batteries included.
100+ permissioned data sources, 250+ research skills, and 25+ built-in expert agents, wired into one fluid system. Compose them yourself, or let an agent pick the right ones for the task. Grep maintains every integration for you.
100+
Data sources
Registries, courts, sanctions and markets, permissioned and ready.
→
250+
Skills
The verified building blocks agents run, each one sourced.
→
25+
Built-in agents
Expert agents that orchestrate skills and sources for you.
Latest white paper
Built to scale.
Not to fail.
Read our latest white paper on why agents fail in production, and what it takes to make them reliable.
Why AI agents fail in production
Most failures begin in the systems around the model. Explore the failure modes and the controls Grep puts around every run.
Where agents fail
Share of classified production incidents · n = 591
What goes wrong
Instructions slip out of context. Old tool results and the wrong case data get carried into the next decision.
Source: white paper, Figure 3
Distribution reported in the paper, citing Clyro and Presenc AI.
The Grep harness
The controls around the model.
Planning
Defined workflowTools
Only the tools neededPermissions
Scoped accessMemory
Saved, then re-readThe model
Right model, each stepContext
One step at a timeRetries
Bounded cost and timeLogging
Every run on recordEscalation
A path to a humanHow Grep addresses it
Grep saves evidence outside the context window and re-reads it when needed. Each workflow step receives the relevant instructions and case record.
How fast-moving companies use Grep.
Shopmonkey- Faster research
- 85%
- More sources
- 3×
- Missed fraud
- 0
Research from hours to minutes.
“Grep helps me make informed decisions faster. With confidence.”
Crystal AndersonOperations Manager · Shopmonkey
Wisdom Ventures- Days replaced
- 8h
- Analyst hires
- 0
- Partners
- 8
Partner meetings with sharper context.
“Effectively filling part of the analyst function as the firm scales.”
Zoë RogersOperating Partner · Wisdom Ventures
Initialized Capital- Saved / workflow
- 3–12h
- Consolidated
- 5+
- On the team
- 4+
Ops research as a repeatable workflow.
“Higher quality and more trustworthy, with sources to back it up, than any tool I've used.”
Vivian ChavesInitialized Capital
Run an agent today.
Or deploy an agent fleet in days.
Try it yourself
Sign up, start on credits, and run an agent the same day without talking to sales. Self-serve runs the same harness, sandboxes, and audit trails as enterprise.
Objective in, running agent out; first run in minutes
Pay-as-you-go credits; right-sized model cost from run one
Keep every agent you tune; export the decision trail anytime
Speak to sales
For teams running agents at volume: a working session against your real workflows and constraints. We size the model mix, the cost ceiling, and the audit requirements with you.
Dedicated deployment; data stays in your perimeter
Volume pricing; compliance review with your risk team
Hands-on onboarding of your first production workflows
Frequently asked questions
Is this a model gateway or a router?
No. A gateway forwards your tokens to whichever model you name; a router load-balances. Grep runs the entire job. It picks the model for each step against your cost ceiling and accuracy floor, executes in isolated sandboxes, and writes the audit trail. The model choice is an output, not your input.
Do I have to talk to sales to try it?
No. Self-serve signup runs an agent the same day, no sales contact. Self-serve is a headline feature, not a consolation path. Enterprise teams spending $50K+/month get a working session. The product is never gated or waitlisted.
Which models do you use?
Claude, GPT, DeepSeek, and secure open-source models, chosen per step. Cheap, fast models handle ingestion and extraction; frontier models are reserved for the steps where accuracy is non-negotiable. You set the constraints; the harness routes.
How is “managed” different from a provider’s managed offering?
A provider optimizes for its own models. It wins when you spend more on them. Grep is not a model. We optimize across all of them for your constraints, and we win when you win. Managed is not Claude-managed.
What do you give compliance and risk teams?
A decision trail on every run: the model chosen, the cost, and the reason for each step, exportable as a file you can hand to a regulator. Sandbox isolation, scoped keys, and SOC 2 (Type II in progress) are standard.
How does pricing work?
Public rates are unpublished by design: pricing tracks the right-sized model mix for your workflows. The calculator above gives a live estimate from your current spend; request your real analysis and we will return exact numbers against your actual model mix and volume.