Aelo vs DIY (in-house build)

TL;DR. The models behind call analytics are a commodity — you can call the same ASR and LLM APIs Aelo uses. What you actually build in a DIY project is everything around them: ingestion from telephony, retries and rate limits, idempotency, diarization, a scoring framework, dashboards for managers, CRM delivery, and cost controls. That layer typically takes months to ship and a fraction of an engineer forever after. Aelo sells that layer for $0–559/month, running inside Bitrix24 from day one.

Quick verdict

Independent comparison written by the Aelo team — we are obviously not neutral here, so we keep the criteria checkable. If your constraints genuinely point to building, build.

Where a DIY build is the better fit

An in-house build is a defensible choice when several of these are true at once:

• AI/ML is a core competency. You already run production ML systems, and conversation analytics is close to your product, not a side tool.
• You have engineers to spare. A realistic build needs a dedicated engineer for months, then ongoing ownership. If that doesn’t compete with roadmap work, the math changes.
• Hard on-premise or data-residency requirements. If recordings may not leave your infrastructure at all, a self-hosted pipeline may be the only option — Aelo is EU-cloud, not on-premise.
• Deep custom modelling. You want to fine-tune models or build analysis logic no off-the-shelf scoring framework expresses.

Where Aelo is the better fit

• You need it working this quarter, not next. Aelo’s onboarding is self-serve: connect Bitrix24 and telephony, pick a scoring profile, and the next call is analysed in minutes.
• Sales managers are the users, not developers. Scorecards with 30+ parameters in eight groups, per-rep dashboards, a review queue, alerts — a manager-facing product, not a JSON endpoint.
• You run on Bitrix24. Aelo ships as a full embedded application: verdicts written onto leads and deals, a Smart Process with the full breakdown, automatic tasks. That integration alone is weeks of DIY work.
• The unglamorous 20% is already done. Retries, rate limits, idempotent processing, speaker diarization, multi-language ASR (50+ languages), queueing at scale — the parts that quietly eat DIY schedules are production-tested.
• Spending stays visible. Every analysis shows its cost; budgets cap and auto-pause processing. A DIY pipeline with no cost guardrails is a silent way to run up an API bill.
• You pay for minutes, not headcount. Plans are $0 to $559/month on one axis — analyzed minutes — with a published per-minute rate beyond the included volume.

The cost reality

The API bill is the cheap part on both sides. The real DIY line items are:

1. Build. A usable MVP — ingestion, transcription, diarization, scoring, storage, a minimal UI — is typically a multi-month project for a senior engineer, not a sprint.
2. Operate. Plan for a standing fraction of an engineer (a quarter to half of one, in practice) for provider API changes, edge cases, telephony quirks, and the dashboard requests managers will keep making.
3. Opportunity. Months of a strong engineer’s time spent rebuilding a commodity layer instead of your product.

For comparison: a year of Aelo Pro is $1,548 (or $1,236 billed annually). Most teams spend more than that on the first weeks of a DIY build — before the first call is ever scored. Run the numbers with your own rates; the gap is usually not close.

Questions to ask before you build

A short checklist we’d ask any team considering DIY — the answers decide the project’s real cost:

• How will you handle provider rate limits and outages — queues, retries, backpressure?
• Is processing idempotent? What prevents double-charging yourself for the same call?
• Who owns diarization quality and multi-language ASR selection?
• Where do sales managers look at results — and who builds and maintains that UI?
• How do you see the cost of a single analysis, and what stops a runaway API bill?
• Who maintains the pipeline in a year, when the engineer who built it moves on?

If those questions have owners and budgets, DIY is viable. If they don’t, they become your operations backlog.

Frequently asked questions

Can’t we build this cheaper ourselves?

The API costs are roughly the same for everyone — that part is a commodity. The difference is the months of engineering to reach production quality and the permanent fraction of an engineer to keep it there. A year of Aelo typically costs less than the first month of a serious build.

We want full control of our data. Doesn’t DIY win?

If “control” means on-premise processing, yes — that is DIY’s strongest argument, and Aelo doesn’t offer on-premise today. If it means access and portability: Aelo exposes an open API, exports everything as JSON/CSV, processes data in the EU under a published DPA, and lets you choose ASR/LLM providers.

Can we start with Aelo and move to our own build later?

Yes. Your transcripts, scores, and scorecard definitions export cleanly. Some teams use Aelo to learn what they actually need from call analytics before deciding whether a custom build is worth it — that’s a cheaper way to write your own spec.

Our stack isn’t Bitrix24. Does DIY make more sense then?

Bitrix24 is where Aelo is deepest today (full embedded app); other CRMs connect via the API and webhooks, with more connectors on the roadmap. If your CRM has no path into Aelo and embedded delivery is non-negotiable, DIY — or waiting — can be the honest answer.

Where can I see live pricing?

Pricing for Aelo is on /en/pricing/ — six tiers from a free plan to Enterprise, priced by analyzed minutes only.