Dactic vs hiring an AI consultant
What does hiring an AI consultant actually buy you?
A consultant sells you three things: an outside view, a process for interviewing your people, and a document at the end. For most companies thinking about AI agents, that document is a roadmap: where agents could help, what to build first, and what it will cost.
The outside view has real value. The process is slow. And the document starts aging the day it is approved.
Traditional consulting: $300,000+ and 6+ months. That is the number to hold every alternative against, including ours.
Why is a 6-month AI roadmap out of date when it lands?
Because the ground moves faster than the engagement. By the time a consultant finishes your AI roadmap, the models have moved five versions. Recommendations written for one generation of tools get implemented on another. Pricing has changed. Work the roadmap scoped as a custom build may now ship as a standard feature.
Your business moved too. The people interviewed in month one work differently by month six. Some have left. A new client rule or a new approver has appeared. The roadmap is a careful snapshot of a company that no longer exists in that form.
None of this is the consultant's fault. It is what happens when discovery is a project with a start date and an end date, instead of something that keeps running.
Why would a services firm say this?
We say it as one. Dactic is a Valere company, and Valere does digital transformation work for clients. As Guy Pistone, CEO of Dactic and Valere, puts it: "Dactic grew out of Valere's digital transformation projects."
At Valere, manual AI discovery took two to three weeks of document reviews and staff interviews, at $5,000 to $7,000. Even at that scale the pattern held. Someone was on vacation, so a piece was missing. Then came the quote for the build, and many founders looked at the price and the timeline and decided not to start. Stretch the same process to a large engagement and the gap between the report and the business only grows.
So we turned discovery into software.
How does Dactic do the same discovery work?
Dactic does the discovery a consultant would do, using the systems you already run and the people who do the work. The flow is short on purpose. Connect your sources, answer a 5 to 7 minute AI interview, and deploy your first agent with one click.
- Connected sources give Dactic the what: documents, threads, tickets and boards in tools like Google, Microsoft, Notion and Jira, read where they already live.
- The AI interview captures the how and the why: the judgment calls, exceptions and check-ins nobody wrote down.
- Recommendations show where an agent would help most, based on your context rather than a generic list of use cases.
- Deploy sends the agent to your AI platform. One click, and about 20 seconds later your agent is in your AI platform.
Dactic builds context in three circles: personal, company and industry, and flags where you work differently from your industry. That is the useful part of a consultant's outside view, and it does not expire when the engagement ends.
How do cost, time and ownership compare?
| Traditional AI consultant | Dactic | |
|---|---|---|
| Cost | $300,000+ | From $750/month |
| Time to first agent | 6+ months, and the engagement may end at a roadmap | First agents live within the onboarding cycle |
| What you own | A report and a roadmap | Deployed agents. Every agent ships with its instructions, context files, skills, tools and model choice. |
| Stays current? | No. It reflects the day it was written. | Yes. Context refreshes every 30 days on Launch, every 14 days on Growth, every 7 days on Pro, and daily or continuously on Enterprise. |
What do you own at the end?
With a consultant, you own a document. Acting on it is a second project, usually with a second budget.
With Dactic, you own working agents, and you can see inside them. You can read and edit every agent's instructions, give it feedback, and see your own context graph.
They are also yours to move.
Works with any model; context in an open, portable format.
Deploy to Claude, OpenAI or monday.com, or to local models through MCP. If your model provider triples its price, move your agents. Their instructions and context go with them.
You stay in control of what runs. Nothing deploys to your AI platform until you approve it. Your agents run in your own AI platform. No compute happens inside Dactic.
How does Dactic stay current after go-live?
A roadmap is finished when it is delivered. Context is never finished.
Context refreshes every 30 days on Launch, every 14 days on Growth, every 7 days on Pro, and daily or continuously on Enterprise. When your business changes in a big way, Dactic runs a short follow-up interview. In Guy Pistone's words: "When business objectives shift, they flow straight into your agents' context and instructions."
That is the difference between paying for a snapshot and paying for a system.
When is an AI consultant still the right call?
Sometimes. Bring one in when:
- You need organization-wide change management, not only agents.
- The core problem is strategy or restructuring, and AI is one input among many.
- You need a custom system no product covers, and you have the budget and the 6+ months.
Even then, start with the context. A consultant who begins with your processes already mapped spends their hours on judgment instead of interviews.
How should you decide?
Ask four questions before you sign anything:
- Do we need a document, or a deployed agent?
- Will the recommendations still hold after five model versions?
- Who owns the instructions and context when the engagement ends?
- How does it stay current when our business changes?
If the answers point to working agents, ownership and context that keeps up, start with Dactic. Rated 4.9/5 on G2. From $750/month.