Service
Custom Agentic AI Development
Agentic AI means software that takes multi-step actions toward a goal rather than answering a single prompt. PrecisionLogic scopes each build as a fixed-fee package and architects it personally. Most packages run between $3,500 and $20,000 and ship in four to eight weeks.
Key takeaways
- An agent differs from a chatbot in one way that matters: it takes action in your systems.
- Fixed fee, scoped up front. Most packages fall between $3,500 and $20,000.
- Architecture and quality review are done by the founder on every build, without exception.
- You do not need a Fractional CTO engagement to buy a build.
- You own the code, prompts, configuration, and documentation.
What is agentic AI, in plain terms?
A chatbot answers. An agent acts.
Give a chatbot a resume and it will summarize it. Give an agent a requisition and it will pull candidates from your ATS, score them against the role, draft outreach in your firm's voice, schedule the ones who respond, and flag the three it is unsure about for a human.
The difference is not model quality. It is that the agent has tools, permissions, memory, and a defined place in a workflow that a person used to own.
Two doors into PrecisionLogic
Some companies need a senior technology voice at the table month over month. Others just need the tool built. Both are legitimate, and they are priced differently.
| Fractional CTO | Agentic AI Build | |
|---|---|---|
| What you get | Ongoing technology leadership and strategy | A scoped system, delivered and shipped |
| Shape | Ongoing engagement, month over month | Fixed fee, per package |
| Who architects it | Matt Miller | Matt Miller |
| Best when | The decisions are the problem | The decision is made and you need it built |
| Typical range | $12,000 to $15,000 per month | $3,500 to $20,000 per package |
They feed each other. A build often surfaces the strategic questions that turn into a Fractional CTO engagement, and Fractional CTO clients use the build arm for capacity beyond what one person's week holds. Compare the Fractional CTO engagement
How the build arm works
Step 01 · Scope
Fixed fee, agreed up front
We map the workflow, confirm the data can support it, and write a specification with acceptance criteria. You get a fixed fee before any work starts. If the scope is wrong for the outcome you want, we say so at this stage rather than after.
Step 02 · Build
Architected and built by the founder
Matt designs the architecture and builds through delivery. PrecisionLogic is the prime on the engagement and is accountable for the result, so you have one relationship rather than a roster to manage.
Step 03 · Quality gate
Nothing ships without review
Every deliverable is reviewed against a written checklist for the package before it reaches you. That review is what separates this from hiring a freelancer directly, where the work arrives with nobody senior having checked it.
Step 04 · Handover
You own it, documented
Code, prompts, configuration, and documentation land in your repositories and your accounts. IP assigns to you. Someone on your team owns the agent, understands what it does, and can turn it off.
You could hire an AI freelancer directly and pay less. What you would not get is someone who sits with your leadership team, understands how the business actually runs, and then decides what to build, what not to build, and whether the thing that came back is actually right. That judgment is the reason the fee is what it is.
Build packages
Fixed fee, scoped before you commit. Payment is 50% at kickoff and 50% on acceptance. Ranges reflect integration depth and how many systems the agent has to touch.
| Package | What it does | Typical range |
|---|---|---|
| ATS or CRM push agent | Sends candidates, contacts, or records into Bullhorn, Loxo, Salesforce, or HubSpot from wherever the work starts | $3,000 to $6,000 |
| Fit ranking and scoring | Scores candidates against a requisition with the reasoning exposed and overrides captured | $5,000 to $9,000 |
| Conversational database search | Ask your candidate or client database a question in plain language instead of building a boolean string | $8,000 to $12,000 |
| Agentic workflow automation | One end-to-end workflow rebuilt around an agent, human in the loop, per workflow | $5,000 to $9,000 |
| Market and BD signal monitoring | Watches careers pages, hiring signals, and public sources, and surfaces what your team should act on | $10,000 to $15,000 |
| Network and relationship matching | Connects who you know to who is hiring, across your own data | $12,000 to $18,000 |
| ATS migration support | Selection, data migration, integration, and cutover for Bullhorn, Loxo, HubSpot, and comparable platforms | $8,000 to $20,000 |
Model and API usage costs are billed to your accounts directly rather than absorbed into the fee, so you can see them and own them. One-time costs such as embedding a large database are quoted separately and passed through at cost.
Larger engagements beyond these ranges are scoped and priced on a case-by-case basis.
Not on the list? Most requests are a variation of something here. Tell us what you are trying to do and you will get a fixed fee or an honest no.
Where agents actually pay off
The pattern is consistent. Agents return the most where work is high volume, rules heavy, and low judgment, and where the inputs already live in a system rather than in somebody's head.
Strong candidates
- Screening, scoring, and ranking against defined criteria
- Data entry, enrichment, and record hygiene across two or more systems
- First-draft generation where a human edits and approves
- Scheduling, reminders, and multi-party coordination
- Compliance documentation and audit trail assembly
- Report assembly and recurring analysis
Weak candidates
- Work where the criteria genuinely change every time
- Decisions with legal or safety exposure and no human in the loop
- Anything where the source data is so poor that a person could not do it either
A meaningful share of failed AI projects are data problems wearing an AI costume. If the source data cannot support the decision you want automated, fixing that comes first, and we will tell you before the invoice rather than after.
Build principles
- Scope to one job. The first agent does one job well. Broad agents fail in ways nobody can debug.
- Human in the loop by default. The first version proposes and a person approves. Autonomy is earned by measured accuracy, not assumed.
- Build on your stack. Agents connect to the ATS, CRM, and data warehouse you already run. We do not sell a platform you have to migrate onto.
- Instrument everything. Every action logged, every override captured. Overrides are the training signal for version two.
- Hand over ownership. Someone on your team owns each agent, understands what it does, and can turn it off. Documented, not verbal.
- Stay neutral. No referral fees, reseller commissions, or platform sponsorships from any AI vendor. Model selection is made per workflow on cost, latency, accuracy, and data residency.
Frequently asked questions
Can I buy a build without a Fractional CTO engagement?
Yes. Agentic AI builds are sold as standalone fixed-fee packages. Some clients start with one build and later add a Fractional CTO engagement, and some never do. Both are fine, and we will not push you toward the larger commitment if the build is what you actually need.
Who actually builds the agents?
Matt Miller scopes the work, designs the architecture, and reviews every deliverable before it ships. PrecisionLogic is the prime on every engagement and is accountable for the result.
How do you make sure the quality holds?
Every package has a written specification and quality checklist the build is reviewed against before it reaches you. Matt is in the work throughout, not just reviewing at the end.
How much does a custom AI agent cost?
Most packages run between $3,500 and $20,000 as a fixed fee, depending on integration depth and how many systems the agent touches. Payment is 50% at kickoff and 50% on acceptance. The fee is fixed, so scope changes go through a change order rather than a surprise invoice.
What is the difference between AI automation and agentic AI?
Automation follows a fixed script and breaks when the input changes. An agent evaluates the situation, chooses among available tools, and adapts. Automation is a rule. An agent is a decision.
How long does it take to build a custom AI agent?
A scoped single-workflow agent with a human in the loop typically ships in four to eight weeks from the end of workflow mapping. Multi-system agents take longer, mostly because of integration and permissions rather than the AI itself.
Do we need clean data before we start?
Not perfect data, but honest data. Part of scoping is establishing whether the source data can support the decision you want automated. If it cannot, fixing that comes first and we will say so before you sign anything.
Will an agent replace our staff?
In practice agents take tasks, not roles. The realistic outcome is that the same headcount handles materially more volume and spends more time on the parts of the job that require judgment. Any vendor promising headcount reduction on a specific timeline is guessing.
Which AI models do you use?
Whichever fits the workflow. We evaluate on cost, latency, accuracy, and data residency per use case, and we architect so models can be swapped without a rebuild. We hold no vendor relationships that would bias that choice.
Who owns the agents you build?
You do. Intellectual property assigns to you, and that chain is papered end to end so ownership arrives clean. Code, prompts, configuration, and documentation live in your repositories and your accounts.
What happens when the models change?
Model deprecations, pricing changes, and capability shifts are routine. Builds are architected so a model swap costs days rather than a rebuild. Ongoing maintenance can be added as a support package or handled inside a Fractional CTO engagement.
Let's talk
A 30-minute discovery call is the fastest way to find out whether an embedded Fractional CTO is the right move right now. If it is not, you still leave with a clearer view of the next 24 months.
Last updated: August 2026