Honest Comparison
Heed AI Solutions vs Traditional Systems Integrators: Two Different Animals.
A CFO recently put two proposals on the same desk. A Big 4 firm bid 350,000 dollars over eight months for a generic AI playbook delivered by a rotating bench of junior consultants. We bid 65,000 dollars over 90 days for a working custom AI agent trained on his actual business. Same company. Same problem. Two completely different animals.
Six dimensions, side by side.
Six differences in plain English.
Pricing model. Bench rate vs fixed fee.
Big 4 bills time and materials at 300 to 500 dollars per hour. The longer the project takes, the more they earn. Heed bids a fixed fee tied to a defined outcome. We are incentivized to ship and to ship clean. If we underestimate, we eat it. That alignment is not a marketing claim, it is in the contract.
Timeline. Eighteen months vs ninety days.
An SI engagement begins with a multi-month discovery, a current state assessment, a future state architecture, a vendor selection, a procurement cycle, and then build. We compress that. Discovery is one week. Proof of concept is two to four weeks. Full production build runs four to twelve weeks after the POC validates the idea.
Team composition. Pyramid vs senior pod.
The partner sells the deal. After signature, you get a manager and three or four analysts, often with offshore augmentation. Heed runs the opposite shape. The principal who scopes the work is the principal who builds it. There is no handoff. There is no second team learning your business on your dollar.
AI capability. Generic vs custom-trained.
Most SI AI practices were built by retraining management consultants on a vendor partnership deck. Their default deliverable is a Microsoft Copilot rollout or a Salesforce Einstein configuration. We build custom agents on top of foundation models, trained on your documents, your workflows, and your terminology. That difference compounds over time.
Post-launch. Handoff vs continuous improvement.
The classic SI playbook is build, train your team, hand it over, and hope the change order comes through next year. We treat go-live as the start. A modest monthly retainer keeps the system improving as your business changes, because AI systems decay if no one tunes them. Optional, but most clients keep us in the loop.
Data and IP. Yours vs theirs.
Big SIs keep their methodology IP and route you onto vendor platforms with recurring licensing. The result is a long tail of vendor lock-in. We write the code in your repository, run it in your cloud account or ours under your tenant, and deliver documentation that your next team can read. If you fire us, you can hire someone else and keep going.
350,000 dollars vs 65,000 dollars. Same problem.
A 60-employee professional services firm wanted an internal AI agent to search project knowledge across SharePoint, a CRM, and 12 years of historical project files. The Big 4 bid was 350,000 dollars over eight months, with the actual build to follow at additional cost. Heed scoped a 30,000 dollar Phase 1 proof of concept, with a path to a 65,000 dollar production build, total elapsed time 90 days from kickoff to live.
The SI bid was a discovery and roadmap. Ours was a working system. Both have a place. But for a CFO doing the math on payback period, 65,000 dollars in 90 days is a different conversation than 350,000 dollars in eight months for slides.
California's largest hillside structural engineering firm.
A 50-plus employee structural engineering firm with offices across California was 85 percent of the way through a Salesforce migration when the team realized the SaaS path was not going to give them what they actually needed: a searchable index of project knowledge spanning plan sets, permits, photos, budgets, and meeting transcripts. They walked away from the SaaS path and brought us in.
We won the engagement in two demo meetings, on the strength of working proofs of concept rather than slides. Phase 1 was 30,000 dollars. We connected Salesforce (live read), SharePoint, Microsoft 365, QuickBooks Time, and the project archive. We built a custom AI agent for project search, image processing for jobsites, transcript analysis for meetings, and document processing for permits. The whole thing ran behind Cloudflare Zero Trust with Microsoft Entra ID single sign-on for roughly 20 users, on ISO 42001-aligned controls.
Outcome. About 80 hours per week of recovered capacity across the team, roughly 24,000 dollars per month in recovered cost, payback in under six weeks, and a 9.6 times return on the Phase 1 investment. A Big 4 firm had quoted between 150,000 and 250,000 dollars for discovery alone. Read the full write-up at the structural engineering case study, and a parallel build for executive intelligence at a Southern California fresh produce distributor and exporter.
An honest look at when SIs still win.
Traditional SIs win when:
- The transformation is 5 million dollars or larger and spans multiple business units, geographies, and ERPs.
- You need deep SAP, Oracle, or Workday vertical expertise plus the change-management muscle to deploy across thousands of users.
- You operate in a regulated industry where specific accreditations (FedRAMP High, HITRUST, defense) gate the procurement.
- Your board or PE sponsor explicitly requires a Big 4 logo on the project for governance or audit reasons.
- You want a single throat to choke for a multi-year program with named partners on the contract.
Heed wins when:
- You are SMB or lower mid-market and need a working AI capability, not a 200-page roadmap.
- You want fixed fees, fixed timelines, and the principal who scoped the work in the room building it.
- You need custom AI agents trained on your data rather than a generic Copilot rollout.
- You want to own the code, the integrations, and the data, with no recurring vendor licenses imposed on you.
- You want to start with a small proof of concept, see it work, and then expand. No 200,000 dollar discovery phase.
Proof of concept first. Always.
The honest reason SI engagements run long is that nobody knows whether the thing will work until it ships. We collapse that risk by leading with a proof of concept. A working demo in two to four weeks, on your data, that either validates the idea or kills it before either of us has spent serious money. If the POC validates, we move into the production build. If it does not, you stop. That is the deal.
For finance and operations leaders considering a build, our Operations Diagnostic maps the highest-leverage AI opportunities in your business and gives you a fixed-fee proposal at the end. CFOs and CEOs evaluating AI investment can also see role-specific framing at Heed AI for CFOs and Heed AI for CEOs.
Related comparisons.
Comparing a Big 4 bid against ours?
Bring the SI proposal to the call. We will walk through it line by line and tell you honestly where they are right, where the budget is padded, and where a fixed-fee custom build is the better answer.