The PSA built for IT consulting

Developer staffing, T&M project management, technical ATS and billing: all in one AI chat that understands the IT lingo.

The specific problems of IT consulting

Selling IT consultants is different: skill stacks change every 6 months, rates vary by seniority, certifications are gold, projects renew or end abruptly.

CVs age fast: continuous stack updates needed
Skill ↔ JD matching done manually
Different rates per client, role, rare skill
Contract renewals lost to missed follow-ups
Bench consultants costing without revenue

A PSA that knows the IT world

hice.ai knows React, Java, Kubernetes, AWS, SAP. When an RFP arrives, AI reads the JD and proposes the best candidates from your database in seconds.

"Find me a Senior React + AWS, available in Rome from January"
"Which Java consultants leave the Intesa project within 60 days?"
"Calculate average market rate for a Senior DevOps"
"Show the bench: who's been unbilled for over 30 days"

Try it in chat

Examples you can ask:

Static demo of hice's AI chat.

What you get

Dynamic skill matrix

Database of technical skills with levels, certifications, project experience.

AI reading of technical JDs

AI extracts technical requirements and matches the consultant database.

Bench management

Real-time visibility on unallocated consultants and staffing actions.

Proactive contract renewals

AI alerts 60 days before client contract expirations.

Dynamic rate card

Price lists by skill, seniority, client, project duration.

Reporting for the CTO

Skill coverage, training gaps, firm stack evolution.

The pace of stack change as a data problem

In technology consulting the skills inventory ages faster than in any other sector. A technology can go from marginal to standard requirement in eighteen months, and the profiles who master it are not the ones who wrote it on a CV but the ones who used it recently.

That forces a living skills model: with a last-used date, a level validated by someone, and reviewable equivalences between technologies in the same family. A static inventory gives a false sense of coverage, and the error surfaces exactly when the request you needed to win arrives.

Date of the last project where each technology was used
Difference between occasional exposure and continuous use
Certifications with expiry and advance warning
Fast addition of new technologies to the vocabulary

Renewals and framework agreements: where predictable growth sits

In technology consulting a significant share of the business is not won but renewed. Yet renewals are usually managed worse than new opportunities, because nobody keeps them in a pipeline and they surface when the client gets in touch, which is sometimes to say they are not continuing.

Treating every expiry as an opportunity with a date, an owner and preparation changes the outcome. The renewal conversation is better prepared with delivery data: hours consumed, incidents, the client's view of the assigned team, and out-of-scope work delivered without charge, which is often the strongest argument available.

Expiry and notice windows visible well in advance
Framework consumption against what was contracted
Delivery evidence attached to the renewal conversation
An owner assigned to every renewal, as with any sale

Bench, rates and margin per consultant

In a resource-supply model the margin turns on two variables that move at different speeds: the sell rate, negotiated per contract and stable for months, and the cost of the person, which moves with salaries, replacements and non-billable hours. When the two do not live in the same system, real margin is known late.

The other factor is unassigned time. A bench day appears on no invoice but very much on payroll, and it is the line that erodes profitability fastest in a growing firm. Measuring it per person and per skill shows where capacity is surplus and where training or repositioning pays.

Sell rate and cost per consultant with history
Unassigned days by person, skill and period
Margin per consultant, per project and per client
Warning on rates out of date against the contract

200-consultant IT body rental — example

The staffing director used to receive 15 RFPs/week. 30 minutes each = 7+ hours weekly just searching. With hice.ai: "Find me the 5 best matches for this JD" → 10 seconds. 7 hours/week freed for closing more deals.

hice.ai vs generalist PSAs for IT

Feature	hice.ai	Generalist PSA
Tech stack knowledge	Native	To be configured
Skill matrix	Dynamic AI	Static table
AI matching JD ↔ CV	Yes	No
Bench management	Dedicated dashboard	Manual report
IT jargon understanding	Yes	No
Time-to-staff	Minutes	Hours or days