Aiguro

Aiguro for Consultancies

a client-ready hypothesis pipeline in a day

Turn a client's documents into a client-ready pipeline of cost and efficiency hypotheses in a day - with reusable methods and one workspace per client. See a real hypothesis card built for a new mandate.

Request access tell us about your team and we will get in touch to set up your workspace.

Hypothesis card: Benchmark and retender Client A's telecom contracts The worked hypothesis from the consultancy sample workspace. Method PR-3 Benchmarking, potential EUR 96,000 to 160,000 (12-20% of EUR 798,000 telecom spend, typical for a first benchmark.), effort 1 of 5, complexity 2 of 5. Supported by client-a-mobile-agreement.md, contradicted by client-a-fixed-line-agreement.md on 'Telecom spend renegotiable within 12 months'. Hypothesis In progress Benchmark and retender Client A's telecom contracts METHOD PR-3 Benchmarking POTENTIAL EFFORT COMPLEXITY EUR 96k - 160k 12-20% of EUR 798,000 telecom spend, typical for a first benchmark. EVIDENCE Supports client-a-mobile-agreement.md Contradicts client-a-fixed-line-agreement.md challenges: Telecom spend renegotiable within 12 months From client-a-cost-baseline.csv Sample workspace, fictitious data

The problem

"Every new mandate starts from a blank slide deck instead of reusing what already worked."

"The proposal phase needs a credible hypothesis pipeline fast, before the contract is even signed."

"Client data has to stay strictly separated, and swapping between engagements slows everything down."

How it works

  1. Upload a client's documents, cost and operations data and contracts into that client's own workspace.
  2. Findings Aiguro's discovery strategies surface signals from the client's documents, news and market events.
  3. Hypotheses findings become structured hypotheses with a method, potential, effort and evidence, ready to present.
  4. Pipeline a client-ready pipeline of levers, exportable into the deliverable format you already use.
How Aiguro works Your business data, documents and market news feed scheduled discovery. Discovery turns them into findings, findings into hypotheses with a method, potential and evidence, and hypotheses into a prioritised pipeline of cost and efficiency levers. Underneath, a knowledge graph remembers every document, finding, decision and rejection, feeds that knowledge back into findings, hypotheses and the pipeline, and steers the next run. Your data Business data Documents News, markets Discovery Scheduled strategies analyse and cross-reference Findings Signals with evidence Hypotheses Method Potential Evidence Pipeline Prioritised Knowledge graph remembers every document, finding, decision and rejection remembered steers the next run

Proof

A worked example from the sample workspace: an anonymised client case turns into a hypothesis pipeline ready for a proposal or a kickoff, with the source documents attached as evidence.

Every hypothesis draws on the same method catalogue across every client workspace, so a lever that worked for one client is one click away on the next. Client data stays isolated: one database per team, EU hosting, no training on customer data.

Why not a chatbot

A generic AI assistant starts every conversation from zero. Aiguro remembers what each client's workspace has uploaded, found, decided and rejected, connecting it all in a knowledge graph - so a method proven with one client does not have to be rebuilt from a blank prompt for the next, and nothing from one client workspace leaks into another.

Value compounds: in week one it looks like a good chatbot; by month three the graph is steering every new analysis and findings arrive without anyone asking. See the full picture on the comparison page.

A chat window forgets, the Aiguro workspace remembers Left: a generic AI assistant starts every session from zero and suggests the same idea again. Right: in an Aiguro workspace every document, finding, hypothesis and rejection is a node in a knowledge graph. One contract supports the hypothesis, another contradicts it, market news supports the finding it was derived from, and a rejected idea that is similar is not proposed again. Generic AI assistant MONDAY Have you tried renegotiating this contract? starts from zero NEXT WEEK Have you tried renegotiating this contract? starts from zero NEXT MONTH Have you tried renegotiating this contract? starts from zero Aiguro workspace Every item becomes a node; enrichment links them supports derived from derived from contradicts similar to supports Contract A Spend export Finding Market news Contract B Rejected idea Hypothesis Not proposed again - already rejected

Pricing

Small Team a flat monthly price, 3 users, 1 shared workspace. Fits a small consulting team piloting the tool on its first client, no seat maths.

Pro priced per user, minimum 3 seats, workspaces scale with seat count, includes SSO. Built for consultancies running several client workspaces in parallel.

Enterprise custom, sales-led, for larger consulting practices, SSO enforcement and negotiated contracts. Includes the Valuedesk integration: connect Valuedesk and export hypotheses to it. Talk to sales.

AI usage runs on a monthly credit budget: 5,000 credits on Small Team, 2,000 credits per user on Pro, custom on Enterprise. Chat, discovery runs and document analysis draw on it in proportion to the AI work they do - a quick question costs a few credits, a deep discovery run more. When the budget is used up, AI features pause until the next billing period or an upgrade.

FAQ: seats and workspaces every user also gets a private default workspace that never counts against your quota; shared workspaces (typically one per client) are what the quota limits.

Security and compliance

Every team gets its own isolated database - never a shared schema. Data is hosted in the EU, and nothing you upload is used to train models. Pro and Enterprise include SSO (Entra ID); role-based access controls who can see and edit each client workspace. A standard Data Processing Agreement (GDPR Art. 28) is available for download, with the sub-processor list published alongside it.

One isolated database per team, hosted in the EU Every team gets its own database, never a shared schema, inside EU hosting, with SSO and role-based access. AI models answer requests from the workspace and are not trained on customer data. EU hosting Your team SSO, role-based access Own database Another team SSO, role-based access Own database Another team SSO, role-based access Own database AI models Answer requests from your workspace No training on your data

FAQ

Can we keep clients strictly separated? Yes - each client gets its own workspace, with role-based access controlling who on your team can see it.

Does it replace our deliverable format? No - hypotheses export into the format you already use for client deliverables; Aiguro is where they are found and validated.

What happens to a client's data when the engagement ends? It stays yours and visible during the read-only period after cancellation; nothing is deleted immediately.

Can we try it before committing? Request access and we will get in touch to find the right way to start with your own documents.