The AI CRM you manage by talking

A CRM where you no longer fill any form: tell the AI what happened with a client, it updates deals, contacts and pipeline. The traditional manual interface is also available.

Why traditional CRMs don't work for consulting

Classic CRMs (Salesforce, HubSpot) are built for product sales. For consulting they become a burden: too many fields, too many screens, zero AI on real project context.

Endless forms no consultant truly fills in
Stale pipelines because updating costs more than selling
No bridge between commercial deal and delivered project
Generic AI that doesn't understand T&M or staffing
Reports that are 2 weeks old by the time you read them

The CRM as a conversation

hice.ai is the first CRM where you talk to AI and AI does the rest: updates deals, drafts follow-ups, computes win probability, prepares the proposal.

«Just closed the call with Generali, meeting again in 10 days with the proposal» → AI updates the deal, creates tasks, drafts the proposal
«Which deals are stuck for over 14 days?» → AI gives you the list with suggested actions
«Generate T&M proposal for the Enel deal at €750/day for 3 seniors» → AI fills everything
«Quarter close forecast» → AI computes deal probabilities from your real history

Try it in chat

Examples you can ask:

Static demo of hice's AI chat.

What you get

Conversational pipeline

Update deals by typing what happened, no more dragging stages.

AI lead scoring

Each lead gets a dynamic score from sector, fit, history and intent signals.

Real-time forecast

Close predictions based on your real consulting history, not generic averages.

Total client memory

AI remembers every call, email and proposal: no more «what did we say?»

Calendar and mail integration

Every meeting and email is absorbed into the pipeline automatically.

AI proposal generation

T&M and fixed-price commercial proposals generated in 30 seconds from a voice or text brief.

Cross-team pipeline

Commercial, delivery and finance see the same truth in real time.

Native automations

Triggers on stage change, deadlines, missing follow-ups: AI acts or alerts you.

AI contact tagging

Industry, role, seniority inferred by AI from signature, LinkedIn and conversations.

Conversational dashboards

Ask any chart in chat: pipeline by industry, hit rate per rep, average cycle.

EU data & GDPR

For sensitive data: EU hosting, encryption at-rest and in-transit, daily backups and audit trail.

Traditional interface

Prefer classic CRM with tables and forms? Always available alongside the AI chat.

Why a product CRM does not fit a consulting sale

A CRM built for product sales assumes a catalogue, a price and a close date. A consulting sale has none of those in a stable form: the deliverable is defined during the conversation, the price depends on which people would be assigned, and the close date depends on a client budget cycle nobody in the pipeline controls.

The consequence is that the standard fields end up holding approximations, and the forecast built on them is decorative. What a consulting pipeline actually needs to record is the shape of the demand — which roles, how many, starting when — because that is what has to be reconciled against the bench.

Required roles and volume recorded on the opportunity
Expected start date, separate from the close date
Probability tied to the client's decision stage
Link between the opportunity and the capacity it would consume

Connecting the pipeline to the bench

The most expensive mistake a growing consulting firm makes is selling work it cannot staff, and the second most expensive is keeping people on the bench for a project that was never going to close. Both come from the same gap: the pipeline and the capacity plan living in different places.

Connecting them does not require certainty, only a weighted view. Opportunities above a probability threshold reserve provisional capacity; below it they appear only as an indication. That is enough to spot the month where three probable projects want the same two seniors, which is a conversation better held in advance.

Provisional capacity reserved by probability
Alert when two probable deals need the same person
Bench visibility for whoever is negotiating dates
Reservation released automatically when a deal is lost

What automation should not touch in a relationship sale

In a consulting sale the differentiator is judgement, and judgement is exactly what generic automation flattens. Sequenced emails to a prospect who has met the partner twice do more damage than no follow-up at all, because they signal that the relationship is being processed.

The useful division is that the system remembers and the person speaks. Automate the reminder that a proposal has been out for eleven days, the note that a client's budget cycle opens next month, the flag that nobody has spoken to a key contact since the summer. Leave every word that reaches the client to the person who owns the relationship.

Reminders internal, messages written by a person
Proposal ageing tracked without automatic chasing
Client budget cycles recorded as an account attribute
One shared history so nobody repeats a conversation

Strategy boutique, 12 sales

A 12-seller strategy boutique used Salesforce. Pipeline update: 4 hours/week per person. With hice.ai sellers update the pipeline by chatting after each call. Admin time: -75%. Hit rate: +18% because forecasts are realistic.

hice.ai vs Salesforce / HubSpot

Feature	hice.ai	Traditional CRMs
Pipeline update	Conversational	Manual forms
Native AI	Yes, acting agent	Generic add-on
Understands T&M	Yes	No
Lead scoring	On real history	Static rules
Forecast	AI probabilistic	Stage-based
Setup time	Days	Months
Total cost of ownership	Lower	Higher