Custom AI agents.
Single-purpose AI agents that do one job well: qualifying inbound leads, drafting first-pass proposals, triaging support tickets, scoring vendors. Built on Claude, OpenAI, or open-source models, configured to your stack. Wired into your CRM, email, and internal APIs. First agent live inside 21 days.
A custom AI agent at Suvysoft is not a chatbot. It is a small, focused system that performs a real workflow inside your business: reading inbound forms, looking up companies in your data warehouse, scoring against a written rubric, drafting a response, and routing to the right person. We build them on Claude, OpenAI, or open-source models like Llama and Mistral, depending on cost, quality, and where your data is allowed to live.
Every agent ships with three things you do not see in most AI consulting work: an evaluation harness with golden datasets and regression tests, a guardrails layer that catches low-confidence cases before they ship to a human, and an observability dashboard that shows latency, cost, and answer quality in real time. We do not deploy agents we cannot measure or roll back.
First agent goes live inside 21 days from kickoff. We start with a workflow audit, then a 21-day pilot with a fixed fee. If the agent does not clear the success bar we set together, you do not pay the production fee.
- Founders and ops leaders watching the team spend hours per week on repeatable knowledge work.
- Sales and customer success teams drowning in inbound that needs qualification or triage.
- Professional services firms (legal, accounting, consulting) whose lead partners are bottlenecked on routing decisions.
- Operators who have tried off-the-shelf AI SaaS tools and watched them misclassify cases that humans get right.
Eight things you get when we deliver an agent.
Workflow mapping
We sit with the team that does the work today, map every step, and identify the right shape for the agent.
Tool wiring
Connect the agent to your CRM, email, calendar, internal APIs, and document store. Real reads and writes, not toy demos.
Prompt and policy library
Versioned prompts, system policies, and refusal rules. Every change tracked, every change reviewed.
Evals and test suites
Golden datasets, regression tests, and adversarial inputs. We do not deploy what we cannot measure.
Guardrails and rollback
Rate limits, escalation paths, kill switches. The agent flags low-confidence cases instead of guessing.
Observability
Per-call logs, latency, cost, and quality metrics on a dashboard you actually open.
Human-in-the-loop UI
When the agent is uncertain, a teammate reviews. Approvals flow back into evals so the system improves.
Tuning retainer
Weekly review, monthly tuning. New tools added as your workflow changes.
From workflow to live agent in three weeks.
Discover
Two-week workflow audit. Sit with the team. Map every step. Find the right agent shape and scope.
Wire
Connect tools and data sources in a sandbox. Read-only first, then write access once tests pass.
Train
Build the prompt library, run evals on real cases, tune until the score crosses the bar we set together.
Deploy
Roll out behind a feature flag. Start with one user, expand to the team, then to production.
Operate
Weekly tuning, monthly review. Metrics dashboard. New capabilities added as the agent earns trust.
Inbound qualification agent saved 18 hours a week.
Inbound leads were being qualified by hand: read the form, look up the company, score it, route it. We delivered a qualification agent that reads the inbound form, enriches against the firm's research stack, scores against a written rubric, and routes to the right partner. Live in 19 days, replaced 18 hours per week of partner time, and surfaced the low-confidence cases for human review instead of guessing.
Before kickoff.
Which AI model do you use?
Where does my data live?
How does the 21-day pilot work?
What if the agent does not work?
Will the agent replace a human?
What is the typical cost?
Tell us the workflow and we will scope an agent.
21-day pilot, fixed fee, evals included. If the agent does not clear the bar, you do not deploy it.