Custom AI agents that do the work, not just talk about it
Goal-driven agents that read, reason and act across your CRM, inbox, docs and APIs, with guardrails and human sign-off where it matters.
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What is an AI agent?
An AI agent is software powered by a large language model that can plan and take actions toward a goal. Unlike a chatbot, it can use tools such as APIs, databases, browsers and business apps, remember context, and decide its next step until the task is done, usually with a human approving high-impact actions.
Most chatbots answer questions. An AI agent finishes jobs. We design and build agents that understand a goal, plan the steps, call your systems through secure tools, check their own work and hand off to a person when confidence is low.
Every agent we ship comes with evaluation suites, audit logs, cost controls and role-based permissions, so your team can trust it in production from day one.
Our offerings
Our senior teams combine proven frameworks, reusable accelerators and hands-on engineering to deliver results at speed and scale.
Get in touch- 01
Customer support agents
Resolve tickets end to end: look up orders, issue refunds within policy, update the CRM and escalate edge cases with full context.
- 02
Sales & SDR agents
Research accounts, enrich leads, draft personalized outreach and book meetings straight into your calendar.
- 03
Operations & back-office agents
Reconcile invoices, process documents, update ERP records and chase approvals across email and Slack.
- 04
Internal knowledge agents
Answer policy, product and engineering questions from your docs with citations, and take action where permitted.
- 05
Multi-agent systems
Specialist agents that collaborate, with an orchestrator that routes work, shares memory and checks results.
- 06
MCP servers & tool integrations
Expose your systems to agents safely through Model Context Protocol servers, function calling and typed APIs.
BufferSol's AI Agents delivery approach
- 01
Job mapping
We pick one high-value job, document the steps, tools and rules, and agree success metrics.
- 02
Prototype in two weeks
A working agent on your real data with an evaluation set that measures accuracy and cost.
- 03
Harden & integrate
Guardrails, approvals, observability, SSO and integrations with your production systems.
- 04
Launch & improve
Staged rollout, live monitoring and continuous tuning from real conversations.
Industry-specific AI Agents solutions
E-commerce
Order-status, returns and product-advice agents that work inside your store and helpdesk.
Healthcare
Intake, scheduling and caregiver-coordination agents with HIPAA-aware data handling.
Real estate
Lead-qualification agents that answer listings questions and book viewings 24/7.
SaaS
In-product copilots that configure settings, explain data and complete tasks for users.
Why BufferSol for AI Agents?
Hours back every week
Agents absorb repetitive research, triage, data entry and follow-ups so specialists focus on judgment calls.
Always-on response
Customers and internal teams get accurate answers and actions in seconds, at any hour, in their language.
Safe by design
Scoped tool access, approval steps, PII redaction and full trace logs keep every action reviewable.
Secure, responsible delivery
Least-privilege access, audit logs and security reviews on every release.
100% IP ownership
You own the code, designs and data. Documented handover, no lock-in.
Senior team, no hand-offs
The engineers who scope your project are the ones who build it.
Technology we use
- Claude
- OpenAI
- Gemini
- LangGraph
- Model Context Protocol
- Vercel AI SDK
- Python
- TypeScript
- pgvector
- LangSmith
Enterprise-ready by default
Security, governance and responsible AI
Autonomous systems only create value when you can trust them. Every agent and platform we ship includes the controls your security, legal and compliance teams expect.
Security by design
Least-privilege access, encrypted data in transit and at rest, secrets in managed vaults and OWASP-aligned code reviews.
Human-in-the-loop AI
Approval gates for high-impact actions, confidence thresholds and clean hand-offs to your team when an agent is unsure.
Guardrails & audit trails
Every agent decision, tool call and data access is logged and traceable, so compliance teams can review what happened and why.
Evaluation & monitoring
Test suites for prompts and models, cost and latency dashboards, and drift alerts before quality slips in production.
Data privacy & compliance
GDPR-ready data handling, NDAs as standard, data residency options and HIPAA-conscious builds for healthcare.
You own everything
Full IP transfer, source code in your repositories and documentation your in-house team can run with.
Related case studies
AI Agents solutions we have designed, built and put into production.
How we engage
Engagement models built around outcomes
Start small, prove value fast and scale what works, with transparent pricing at every stage.
2–3 weeks
AI Discovery Sprint
Map your processes, rank automation opportunities by ROI and leave with a working prototype and a costed roadmap.
- ✓Process & data audit
- ✓Use-case scoring
- ✓Clickable or working prototype
- ✓Fixed price
6–16 weeks
Build & Launch
A dedicated squad designs, builds, tests and launches your agent, workflow or product, with weekly demos and a fixed scope.
- ✓Product, design & engineering
- ✓Weekly demos
- ✓QA, security & evaluation
- ✓Production launch
Monthly
Run & Scale
We operate, monitor and improve what we built: model updates, new automations, SLAs and 24/7 support.
- ✓Monitoring & evaluation
- ✓Continuous improvement
- ✓SLA-backed support
- ✓Dedicated team option
How long does it take to build an AI agent?
A focused production agent typically takes 4 to 8 weeks: about two weeks to a working prototype on your data, then hardening, integrations and a staged launch. Multi-agent systems with many integrations take longer.
How much does a custom AI agent cost?
Cost depends on the number of tools, integrations and compliance requirements. We scope a fixed-price discovery and prototype first, so you see results on your own data before committing to a full build.
Which AI models do you use?
We are model-agnostic. We benchmark Claude, GPT, Gemini and open-weight models on your tasks and choose based on accuracy, latency, cost and data-residency needs. You can switch models later without a rewrite.
How do you keep AI agents from making costly mistakes?
Agents get the minimum tool permissions they need, high-impact actions require human approval, outputs are checked against rules and every step is logged. We also run automated evaluation suites before each release.
Can an AI agent work with our existing software?
Yes. Agents connect to CRMs, helpdesks, ERPs, databases, email, Slack and custom APIs through secure tool integrations or MCP servers. If a system has an API, or even just a web interface, we can usually connect it.
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Let's build what's next, together.
Tell us what you want to automate or build. A senior engineer will reply within one business day.
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